Dataset Information

Multi-scale characterizations of colon polyps via computed tomographic colonography.

ABSTRACT: Texture features have played an essential role in the field of medical imaging for computer-aided diagnosis. The gray-level co-occurrence matrix (GLCM)-based texture descriptor has emerged to become one of the most successful feature sets for these applications. This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor. In this study, we first introduce a new parameter - stride, to explore the definition of GLCM. Then we propose three multi-scaling GLCM models according to its three parameters, (1) learning model by multiple displacements, (2) learning model by multiple strides (LMS), and (3) learning model by multiple angles. These models increase the texture information by introducing more texture patterns and mitigate direction sparsity and dense sampling problems presented in the traditional Haralick model. To further analyze the three parameters, we test the three models by performing classification on a dataset of 63 large polyp masses obtained from computed tomography colonoscopy consisting of 32 adenocarcinomas and 31 benign adenomas. Finally, the proposed methods are compared to several typical GLCM-texture descriptors and one deep learning model. LMS obtains the highest performance and enhances the prediction power to 0.9450 with standard deviation 0.0285 by area under the curve of receiver operating characteristics score which is a significant improvement.

SUBMITTER: Cao W

PROVIDER: S-EPMC7099560 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Multi-scale characterizations of colon polyps via computed tomographic colonography.

Cao Weiguo W Pomeroy Marc J MJ Gao Yongfeng Y Barish Matthew A MA Abbasi Almas F AF Pickhardt Perry J PJ Liang Zhengrong Z

Visual computing for industry, biomedicine, and art 20191227 1

Texture features have played an essential role in the field of medical imaging for computer-aided diagnosis. The gray-level co-occurrence matrix (GLCM)-based texture descriptor has emerged to become one of the most successful feature sets for these applications. This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor. In this study, we first introduce a new parameter - stride, to explore the definition of GL ...[more]

PMID: 32240410

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Project description:BackgroundThe Centers for Medicare and Medicaid Services (CMS) considered whether to reimburse computed tomographic colonography (CTC) for colorectal cancer screening of Medicare enrollees. To help inform its decision, we evaluated the reimbursement rate at which CTC screening could be cost-effective compared with the colorectal cancer screening tests that are currently reimbursed by CMS and are included in most colorectal cancer screening guidelines, namely annual fecal occult blood test (FOBT), flexible sigmoidoscopy every 5 years, flexible sigmoidoscopy every 5 years in conjunction with annual FOBT, and colonoscopy every 10 years.MethodsWe used three independently developed microsimulation models to assess the health outcomes and costs associated with CTC screening and with currently reimbursed colorectal cancer screening tests among the average-risk Medicare population. We assumed that CTC was performed every 5 years (using test characteristics from either a Department of Defense CTC study or the National CTC Trial) and that individuals with findings of 6 mm or larger were referred to colonoscopy. We computed incremental cost-effectiveness ratios for the currently reimbursed screening tests and calculated the maximum cost per scan (ie, the threshold cost) for the CTC strategy to lie on the efficient frontier. Sensitivity analyses were performed on key parameters and assumptions.ResultsAssuming perfect adherence with all tests, the undiscounted number life-years gained from CTC screening ranged from 143 to 178 per 1000 65-year-olds, which was slightly less than the number of life-years gained from 10-yearly colonoscopy (152-185 per 1000 65-year-olds) and comparable to that from 5-yearly sigmoidoscopy with annual FOBT (149-177 per 1000 65-year-olds). If CTC screening was reimbursed at $488 per scan (slightly less than the reimbursement for a colonoscopy without polypectomy), it would be the most costly strategy. CTC screening could be cost-effective at $108-$205 per scan, depending on the microsimulation model used. Sensitivity analyses showed that if relative adherence to CTC screening was 25% higher than adherence to other tests, it could be cost-effective if reimbursed at $488 per scan.ConclusionsCTC could be a cost-effective option for colorectal cancer screening among Medicare enrollees if the reimbursement rate per scan is substantially less than that for colonoscopy or if a large proportion of otherwise unscreened persons were to undergo screening by CTC.

Project description:BackgroundThe Chinese Society of Clinical Oncology guidelines 2018 and the recent update of that (version 2020) recommends accurate examination before major treatment for decision(s) in cases of colon cancer. Also, the difficulty in the identification of the lesion during colectomy may lead to resection of a wrong segment of the colon or a more extensive resection than planned. Accurate pre-colectomy local staging of colon cancer is required to make decisions for treatment of colon cancer. The objective of the study was to evaluate the diagnostic performance of the computed tomography colonography (CTC) for pre-colectomy tumor location and tumor, node, and metastasis (TNM) staging of colon cancer.MethodsData of preoperative colonoscopies, CTC, surgeries, and surgical pathology of a total of 269 patients diagnosed with colon cancer by colonoscopy and biopsy and underwent pre-colectomy location and TNM staging by CTC were collected and analyzed. The consistency between the radiological and the surgery/surgical-pathological for location and TN stages of colon tumor were estimated with the weighted kappa or kappa coefficient (κ) at 95% confidence interval (CI).ResultsCTC detected 261 (93%) and colonoscopy detected 201 (72%) correct locations of tumors. Sensitivity and accuracy of CTC for detection of location of colon tumors were 100% and 92.58% (κ = 0.89; 95% Cl: 0.83-0.95). 72.48% sensitivity, 90.64% specificity, and 83.57% accuracy were reported for CTC in differentiation of tumors confined to the colon wall (T1/T2) from advanced tumors (T3/T4) (κ = 0.69, 95% Cl: 0.51-0.75). 81.01% sensitivity, 89.11% specificity, and 83.93% accuracy of CTC was reported for differentiation of tumors between low-intermediate risk and high risk (κ = 0.68, 95% Cl: 0.53-0.75). 69.31% sensitivity, 66.15% specificity, and 67.14% accuracy of CTC were reported for N staging of tumors (κ = 0.41, 95% Cl: 0.59-0.69).ConclusionsCTC has high diagnostic parameters for pre-colectomy location and T staging of colon tumors except patients of colon cancer who received neoadjuvant chemotherapy.Level of evidenceIII.Technical efficacy stage2.

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Multi-scale characterizations of colon polyps via computed tomographic colonography.

Publications

Multi-scale characterizations of colon polyps via computed tomographic colonography.

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