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    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 11, No. 1 ( 2021-01-22)
    Abstract: T 2 -weighted (T 2 W) MRI provides high spatial resolution and tissue-specific contrast, but it is predominantly used for qualitative evaluation of prostate anatomy and anomalies. This retrospective multicenter study evaluated the potential of T 2 W image-derived textural features for quantitative assessment of peripheral zone prostate cancer (PCa) aggressiveness. A standardized preoperative multiparametric MRI was performed on 87 PCa patients across 6 institutions. T 2 W intensity and apparent diffusion coefficient (ADC) histogram, and T 2 W textural features were computed from tumor volumes annotated based on whole-mount histology. Spearman correlations were used to evaluate association between textural features and PCa grade groups (i.e. 1–5). Feature utility in differentiating and classifying low-(grade group 1) vs. intermediate/high-(grade group ≥ 2) aggressive cancers was evaluated using Mann–Whitney U-tests, and a support vector machine classifier employing “hold-one-institution-out” cross-validation scheme, respectively. Textural features indicating image homogeneity and disorder/complexity correlated significantly ( p   〈  0.05) with PCa grade groups. In the intermediate/high-aggressive cancers, textural homogeneity and disorder/complexity were significantly lower and higher, respectively, compared to the low-aggressive cancers. The mean classification accuracy across the centers was highest for the combined ADC and T 2 W intensity-textural features (84%) compared to ADC histogram (75%), T 2 W histogram (72%), T 2 W textural (72%) features alone or T 2 W histogram and texture (77%), T 2 W and ADC histogram (79%) combined. Texture analysis of T 2 W images provides quantitative information or features that are associated with peripheral zone PCa aggressiveness and can augment their classification.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2615211-3
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