Comparison between borderline ovarian tumors and carcinomas using semi-automated histogram analysis of diffusion-weighted imaging: focusing on solid components.

Purpose: This study aimed to evaluate whether histogram analysis of the apparent diffusion coefficient (ADC) of a solid tumor component could distinguish borderline ovarian tumors from ovarian carcinoma.Materials and Methods: Sixteen pathologically proven borderline tumors and 21 carcinomas were ret...

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Publicado en:Japanese Journal of Radiology Vol. 34; no. 3; pp. 229 - 238
Autores principales: Mimura, Rie, Kato, Fumi, Tha, Khin, Kudo, Kohsuke, Konno, Yosuke, Oyama-Manabe, Noriko, Kato, Tatsuya, Watari, Hidemichi, Sakuragi, Noriaki, Shirato, Hiroki, Tha, Khin Khin
Formato: research Journal Article
Publicado: Springer Nature Mar2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2016
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      pub: Springer Nature
      place: New York, New York
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        atl: Comparison between borderline ovarian tumors and carcinomas using semi-automated histogram analysis of diffusion-weighted imaging: focusing on solid components.
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          Mimura, Rie
          Kato, Fumi
          Tha, Khin
          Kudo, Kohsuke
          Konno, Yosuke
          Oyama-Manabe, Noriko
          Kato, Tatsuya
          Watari, Hidemichi
          Sakuragi, Noriaki
          Shirato, Hiroki
          Tha, Khin Khin
        affil: Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, N15, W7, Kita-ku Sapporo 060-8638 Japan
      sug:
        subj:
          Magnetic Resonance Imaging Methods
          Ovarian Neoplasms
          Carcinoma
          Image Interpretation, Computer Assisted Methods
          Female
          ROC Curve
          Human
          Diagnosis, Differential
          Young Adult
          Sensitivity and Specificity
          Aged
          Ovary
          Pharmacokinetics
          Retrospective Design
          Middle Age
          Adult
          Aged, 80 and Over
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Aged: 65+ years
          Middle Aged: 45-64 years
          Adult: 19-44 years
          Aged, 80 & over
          Female
      ab: Purpose: This study aimed to evaluate whether histogram analysis of the apparent diffusion coefficient (ADC) of a solid tumor component could distinguish borderline ovarian tumors from ovarian carcinoma.Materials and Methods: Sixteen pathologically proven borderline tumors and 21 carcinomas were retrospectively examined. Magnetic resonance (1.5-T) image data sets were coregistered, and the solid components of each tumor were semiautomatically segmented. ADC histograms of the solid components were extracted; modes, minimums, means, and 10th, 25th, 50th, 75th, and 90th percentiles of the histograms were compared between the two tumor types, and receiver-operating characteristic (ROC) analysis was performed.Results: The mode, minimum, mean, 10th, 25th, 50th, and 75th percentile ADC values of solid components of borderline tumors were significantly larger than those of carcinomas. Among these, the 10th percentile values had the lowest p value (p = 0.0003). At ROC analysis, the area under the curve (AUC) in the 10th percentile was the greatest (0.854), and the best cutoff value in the 10th percentile provided the highest specificity (93.8 %).Conclusions: ADC histograms of solid tumor components facilitated the distinction between borderline ovarian tumors and carcinoma. The 10th percentile ADC values had the best diagnostic performance.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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