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BackgroundEsophageal cancer management lacks reliable response predictors to chemotherapy. In this study we evaluated the feasibility and accuracy of Biodynamic Imaging (BDI), a technology that employs digital holography as a rapid predictor of chemotherapy sensitivity in locoregional esophageal adenocarcinoma. MethodsPre-treatment endoscopic pinch biopsies were collected from patients with esophageal adenocarcinoma during standard staging procedures. BDI analyzed the tumor samples and assessedin vitrochemotherapy sensitivity. BDI sensitivity predictions were compared to patients’ pathological responses, the gold standard for determining clinical response, in the surgically treated subset (n=18). ResultBDI was feasible with timely tissue acquisition, collection, and processing in all 30 enrolled patients and successful BDI analysis in 28/29 (96%) eligible. BDI accurately predicted chemotherapy response in 13/18 (72.2%) patients using a classifier for complete, marked, and partial/no-response. BDI technology had 100% negative predictive value for complete pathological response hence identifying patients unlikely to respond to treatment. ConclusionBDI technology can potentially predict patients’ response to platinum chemotherapy. Additionally, this technology represents a promising step towards optimizing treatment strategies for esophageal adenocarcinoma patients by pre-emptively identifying non-responders to conventional platinum-based chemotherapy. 

Abstract Nearly half of cancer patients who receive standard-of-care treatments fail to respond to their first-line chemotherapy, demonstrating the pressing need for improved methods to select personalized cancer therapies. Low-coherence digital holography has the potential to fill this need by performing dynamic contrast OCT on living cancer biopsies treated ex vivo with anti-cancer therapeutics. Fluctuation spectroscopy of dynamic light scattering under conditions of holographic phase stability captures ultra-low Doppler frequency shifts down to 10 mHz caused by light scattering from intracellular motions. In the comparative preclinical/clinical trials presented here, a two-species (human and canine) and two-cancer (esophageal carcinoma and B-cell lymphoma) analysis of spectral phenotypes identifies a set of drug response characteristics that span species and cancer type. Spatial heterogeneity across a centimeter-scale patient biopsy sample is assessed by measuring multiple millimeter-scale sub-samples. Improved predictive performance is achieved for chemoresistance profiling by identifying red-shifted sub-samples that may indicate impaired metabolism and removing them from the prediction analysis. These results show potential for using biodynamic imaging for personalized selection of cancer therapy.