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Acad Radiol ; 26(1): 30-37, 2019 01.
Artigo em Inglês | MEDLINE | ID: mdl-29566994

RESUMO

RATIONALE AND OBJECTIVES: To (1) apply a quantitative volumetric textural analysis (VTA) to colorectal masses at CT colonography (CTC) for the differentiation of malignant and benign lesions and to (2) compare VTA with human performance. MATERIALS AND METHODS: A validated, quantitative VTA method was applied to 63 pathologically proven colorectal masses (mean size, 4.2 cm; range, 3-8 cm) at noncontrast CTC in 59 adults (mean age, 66.5 years; range, 45.9-91.6 years). Fifty-one percent (32/63) of the masses were invasive adenocarcinoma, and the remaining 49% (31/63) were large benign adenomas. Three readers with CTC experience independently assessed the likelihood of malignancy using a 5-point scale (1 = definitely benign, 2 = probably benign, 3 = indeterminate, 4 = probably malignant, 5 = definitely malignant). Areas under the curve (AUCs) and accuracy levels were compared. RESULTS: VTA achieved optimal sensitivity of 83.6% vs 91.7% for human readers (P = .034), with specificities of 87.5% and 77.4%, respectively (P = .007). No significant difference in overall accuracy was seen between VTA and human readers (85.5% vs 84.7%, P = .753). The AUC for differentiating benign and malignant lesions was 0.936 for VTA and 0.917 for human readers. Intraclass correlation coefficient among the human readers was 0.76, indicating good to excellent agreement. CONCLUSION: VTA demonstrates excellent performance for distinguishing benign from malignant colorectal masses (≥3 cm) at CTC, comparable yet potentially complementary to experienced human performance.


Assuntos
Adenocarcinoma/diagnóstico por imagem , Adenoma/diagnóstico por imagem , Colonografia Tomográfica Computadorizada , Neoplasias Colorretais/diagnóstico por imagem , Neoplasias Colorretais/patologia , Processamento de Imagem Assistida por Computador/métodos , Adenocarcinoma/patologia , Adenoma/patologia , Idoso , Idoso de 80 Anos ou mais , Área Sob a Curva , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Curva ROC
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