Dataset Information

Quantitative analysis of in vivo high-resolution microendoscopic images for the detection of neoplastic colorectal polyps.

ABSTRACT: Colonoscopy is routinely performed for colorectal cancer screening but lacks the capability to accurately characterize precursor lesions and early cancers. High-resolution microendoscopy (HRME) is a low-cost imaging tool to visualize colorectal polyps with subcellular resolution. We present a computer-aided algorithm to evaluate HRME images of colorectal polyps and classify neoplastic from benign lesions. Using histopathology as the gold standard, clinically relevant features based on luminal morphology and texture are quantified to build the classification algorithm. We demonstrate that adenomatous polyps can be identified with a sensitivity and specificity of 100% and 80% using a two-feature linear discriminant model in a pilot test set. The classification algorithm presented here offers an objective framework to detect adenomatous lesions in the colon with high accuracy and can potentially improve real-time assessment of colorectal polyps.

SUBMITTER: Tang Y

PROVIDER: S-EPMC6276307 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Quantitative analysis of in vivo high-resolution microendoscopic images for the detection of neoplastic colorectal polyps.

Tang Yubo Y Polydorides Alexandros D AD Anandasabapathy Sharmila S Richards-Kortum Rebecca R RR

Journal of biomedical optics 20181101 11

Colonoscopy is routinely performed for colorectal cancer screening but lacks the capability to accurately characterize precursor lesions and early cancers. High-resolution microendoscopy (HRME) is a low-cost imaging tool to visualize colorectal polyps with subcellular resolution. We present a computer-aided algorithm to evaluate HRME images of colorectal polyps and classify neoplastic from benign lesions. Using histopathology as the gold standard, clinically relevant features based on luminal mo ...[more]

PMID: 30460794

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Project description:Introduction"Resect and discard" paradigm is one of the main strategies to deal with colorectal diminutive polyps after optical diagnosis. However, there are risks that unrecognized potentially malignant lesions are discarded without accurate diagnosis. The purpose of this study is to validate the potential of micro-optical coherence tomography (μOCT) to improve the diagnostic accuracy of colorectal lesions and help endoscopists make better clinical decision without additional pathology costs.MethodsFresh tissue samples were obtained from patients with colorectal polyps or colorectal cancer who received endoscopic therapy or laparoscopic surgery. These samples were instantly imaged by μOCT and then sent to pathological evaluation. Then, μOCT images were compared with corresponding HE sections. We created consensus μOCT image criteria and then tested to determine sensitivity, specificity, and accuracy of our system to discriminate neoplastic polyps from non-neoplastic polyps.ResultsOur μOCT system achieved a resolution of 2.0 μm in both axial and lateral directions, clearly illustrated both cross-sectional and en face subcellular-level microstructures of colorectal lesions ex vivo, demonstrating distinctive patterns for inflammatory granulation tissue, hyperplastic polyp, adenoma, and cancerous tissue. For the 58 cases of polyps, the accuracy of the model was 94.83% (95% confidence interval [CI], 85.30%-98.79%), the sensitivity for identification of adenomas was 96.88% (95% CI, 82.89%-99.99%), and the specificity was 92.31% (95% CI, 74.74%-98.98%). Our diagnostic criteria could help both expert endoscopists and nonexpert endoscopists to identify neoplastic from non-neoplastic polyps with satisfactory accuracy and good interobserver agreement.DiscussionWe propose a new strategy using μOCT to differentiate benign polyps and adenomas after the lesions are resected. The application of μOCT can potentially reduce the cost of pathological examination and minimize the risk of discarding malignant lesions during colonosocpy examination.

Project description:ObjectivesTo introduce a fully-automated algorithm for the detection of small cortical interruptions (≥0.246mm in diameter) on high resolution peripheral quantitative computed tomography (HR-pQCT) images, and to investigate the additional value of manual correction of the automatically obtained contours (semi-automated procedure).MethodsTen metacarpophalangeal joints from seven patients with rheumatoid arthritis (RA) and three healthy controls were imaged with HR-pQCT. The images were evaluated by an algorithm according to the fully- and semi-automated procedure for the number and surface of interruptions per joint. Reliability between the fully- and semi-automated procedure and between two independent operators was tested using intra-class correlation coefficient (ICC) and the proportion of matching interruptions. Validity of single interruptions detected was tested by comparing it to visual scoring, as gold standard. The positive predictive value (PPV) and sensitivity were calculated.ResultsThe median number of interruptions per joint was 14 (range 2 to 59) and did not significantly differ between the fully- and semi-automated procedure (p = 0.37). The median interruption surface per joint was significantly higher with the fully- vs. semi-automated procedure (respectively, 8.6mm2 vs. 5.8mm2 and 6.1mm2, p = 0.01). Reliability was almost perfect between the fully- and semi-automated procedure for both the number and surface of interruptions (ICC≥0.95) and the proportion of matching interruptions was high (≥76%). Also the inter-operator reliability was almost perfect (ICC≥0.97, proportion of matching interruptions 92%). The PPV ranged from 27.6% to 29.9%, and sensitivity from 69.7% to 76.3%. Most interruptions detected with the algorithm, did show an interruption on a 2D grayscale image. However, this interruption did not meet the criteria of an interruption with visual scoring.ConclusionThe algorithm for HR-pQCT images detects cortical interruptions, and its interruption surface. Reliability and validity was comparable for the fully- and semi-automated procedures. However, we advise the use of the semi-automated procedure to assure quality. The algorithm is a promising tool for a sensitive and objective assessment of cortical interruptions in finger joints assessed by HR-pQCT.

Dataset Information

Quantitative analysis of in vivo high-resolution microendoscopic images for the detection of neoplastic colorectal polyps.

Publications

Quantitative analysis of in vivo high-resolution microendoscopic images for the detection of neoplastic colorectal polyps.

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