Browsing by Author "Parikh, Neil D."

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    In vivo classification of colorectal neoplasia using high-resolution microendoscopy: Improvement with experience
    (Wiley, 2015) Parikh, Neil D.; Perl, Daniel; Lee, Michelle H.; Chang, Shannon S.; Polydorides, Alexandros D.; Moshier, Erin; Godbold, James; Zhou, Elinor; Mitcham, Josephine; Richards-Kortum, Rebecca; Anandasabapathy, Sharmila; Bioengineering
    Background and Aims: High-resolution microendoscopy (HRME) is a novel, low-cost “optical biopsy” technology that allows for subcellular imaging. The study aim was to evaluate the learning curve of HRME for the differentiation of neoplastic from non-neoplastic colorectal polyps. Methods: In a prospective cohort fashion, a total of 162 polyps from 97 patients at a single tertiary care center were imaged by HRME and classified in real time as neoplastic (adenomatous, cancer) or non-neoplastic (normal, hyperplastic, inflammatory). Histopathology was the gold standard for comparison. Diagnostic accuracy was examined at three intervals over time throughout the study; the initial interval included the first 40 polyps, the middle interval included the next 40 polyps examined, and the final interval included the last 82 polyps examined. Results: Sensitivity increased significantly from the initial interval (50%) to the middle interval (94%, P = 0.02) and the last interval (97%, P = 0.01). Similarly, specificity was 69% for the initial interval but increased to 92% (P = 0.07) in the middle interval and 96% (P = 0.02) in the last interval. Overall accuracy was 63% for the initial interval and then improved to 93% (P = 0.003) in the middle interval and 96% (P = 0.0007) in the last interval. Conclusions: In conclusion, this in vivo study demonstrates that an endoscopist without prior colon HRME experience can achieve greater than 90% accuracy for identifying neoplastic colorectal polyps after 40 polyps imaged. HRME is a promising modality to complement white light endoscopy in differentiating neoplastic from non-neoplastic colorectal polyps.
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    Quantitative analysis of high-resolution microendoscopic images for diagnosis of neoplasia in patients with Barrett’s esophagus
    (Elsevier, 2016) Shin, Dongsuk; Lee, Michelle H.; Polydorides, Alexandros D.; Pierce, Mark C.; Vila, Peter M.; Parikh, Neil D.; Rosen, Daniel G.; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca R.; Bioengineering
    Background and Aims: Previous studies show that microendoscopic images can be interpreted visually to identify the presence of neoplasia in patients with Barrett’s esophagus (BE), but this approach is subjective and requires clinical expertise. This study describes an approach for quantitative image analysis of microendoscopic images to identify neoplastic lesions in patients with BE. Methods: Images were acquired from 230 sites from 58 patients by using a fiberoptic high-resolution microendoscope during standard endoscopic procedures. Images were analyzed by a fully automated image processing algorithm, which automatically selected a region of interest and calculated quantitative image features. Image features were used to develop an algorithm to identify the presence of neoplasia; results were compared with a histopathology diagnosis. Results: A sequential classification algorithm that used image features related to glandular and cellular morphology resulted in a sensitivity of 84% and a specificity of 85%. Applying the algorithm to an independent validation set resulted in a sensitivity of 88% and a specificity of 85%. Conclusions: This pilot study demonstrates that automated analysis of microendoscopic images can provide an objective, quantitative framework to assist clinicians in evaluating esophageal lesions from patients with BE. (Clinical trial registration number: NCT01384227 and NCT02018367.)