Diagnostic accuracy of the Clear Cell Likelihood Score and selected MRI parameters in the characterization of indeterminate renal masses – a single-institution study.

Purpose: We aimed to assess the diagnostic accuracy of the clear cell likelihood score (ccLS) and value of other selected magnetic resonance imaging (MRI) features in the characterization of indeterminate small renal masses (SRMs). Methods: Fifty patients with indeterminate SRMs discovered on MRI be...

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Publicado en:Abdominal Radiology Vol. 49; no. 11; pp. 3893 - 3902
Autores principales: Blachura, Tomasz, Matusik, Patrycja S., Kowal, Aleksander, Radzikowska, Julia, Jarczewski, Jarosław D., Skiba, Łukasz, Popiela, Tadeusz J., Chrzan, Robert
Formato: Journal Article
Publicado: Springer Nature Nov2024
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov2024
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00261-024-04484-5
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        atl: Diagnostic accuracy of the Clear Cell Likelihood Score and selected MRI parameters in the characterization of indeterminate renal masses – a single-institution study.
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        au:
          Blachura, Tomasz
          Matusik, Patrycja S.
          Kowal, Aleksander
          Radzikowska, Julia
          Jarczewski, Jarosław D.
          Skiba, Łukasz
          Popiela, Tadeusz J.
          Chrzan, Robert
        affil: Department of Diagnostic Imaging, University Hospital, 30-688, Kraków, Poland
      sug:
      ab: Purpose: We aimed to assess the diagnostic accuracy of the clear cell likelihood score (ccLS) and value of other selected magnetic resonance imaging (MRI) features in the characterization of indeterminate small renal masses (SRMs). Methods: Fifty patients with indeterminate SRMs discovered on MRI between 2012 and 2023 were included. The ccLS for the characterization of clear cell renal cell carcinoma (ccRCC) was calculated and compared to the final diagnosis (ccRCC vs. 'all other' masses). Results: The ccLS = 5 had a satisfactory accuracy of 64.0% and a very high specificity of 96.3%; however, its sensitivity of 26.1% was relatively low. Receiver operating curve (ROC) analysis revealed that from the selected MRI features, only T1 ratio and arterial to delayed enhancement (ADER) were good discriminators between ccRCC and other types of renal masses (area under curve, AUC = 0.707, p = 0.01; AUC = 0.673, p = 0.03; respectively). The cut-off points determined in ROC analysis using the Youden index were 0.73 (p = 0.01) for T1 ratio and 0.99 for ADER (p = 0.03). The logistic regression model demonstrated that ccLS = 5 and T1 ratio (OR = 15.5 [1.1-218.72], p = 0.04; OR = 0.002 [0.00-0.81], p = 0.04) were significant predictors of ccRCC. Conclusions: The ccLS algorithm offers an encouraging method for the standardization of imaging protocols to aid in the diagnosis and management of SRMs in daily clinical practice by enhancing detectability of ccRCC and reducing the number of unnecessary invasive procedures for benign or indolent lesions. However, its diagnostic performance needs multi-center large cohort studies to validate it before it can be incorporated as a diagnostic algorithm and will guide future iterations of clinical guidelines. The retrospective nature of our study and small patient population confined to a single clinical center may impact the generalizability of the results; thus, future studies are required to define whether employment of the T1 ratio or ADER parameter may strengthen the diagnostic accuracy of ccRCC diagnosis.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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