Objective <p>To investigate the potential of multiparametric MRI clear cell likelihood scores (ccLS) for differentiating between fat-poor angiomyolipoma (AML) and clear cell renal cell carcinoma (ccRCC) in subcentimeter Lesions (1&#xa0;cm or smaller).</p> Materials and methods <p>This retrospective study included consecutive patients with subcentimeter renal masses who underwent multiparametric MRI between September 2009 and September 2022 across three hospitals. Clinical and MRI findings were analyzed to differentiate between fat-poor AML and ccRCC. Lesions were categorized using the ccLS and receiver operating characteristic curve analysis was performed to assess ccLS performance.</p> Results <p>Thirty-eight patients (mean age: 52 years ± 12; 19 women) with 39 lesions were included. Of the 39 lesions [mean size: 9.1&#xa0;mm ± 1.0 (range, 6.0–10.0&#xa0;mm)], 20 (51%) were ccRCC and 19 (49%) were fat-poor AML. Compared to the ccRCC, subcentimeter fat-poor AMLs were more likely to show hypointensity on T2WI (<i>P</i> &lt; 0.001), homogeneous enhancement (<i>P</i> = 0.010), the presence of microscopic fat (<i>P</i> = 0.036), and the absence of a pseudocapsule (<i>P</i> = 0.020). The diagnostic percentage of fat-poor AML was 47% for a ccLS of 1 or 2, and ccRCC accounted for 75% in the ccLS 4 or 5 category. The AUC for discrimination was 0.846 (95% CI: 0.695–0.941, <i>P</i> &lt; 0.001), with a sensitivity of 75.00% (95% CI: 50.9–91.3) and a specificity of 89.47% (95% CI: 66.9–98.7).</p> Conclusion <p>Multiparametric MRI clear cell likelihood scores can potentially be used to differentiate between fat-poor AML and ccRCC in lesions 1&#xa0;cm or smaller.</p>

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Can multiparametric MRI clear cell likelihood scores differentiate fat-Poor AML from CcRCC in subcentimeter lesions?

  • Ying Xiong,
  • Yinglong Guo,
  • Xiaoxia Li,
  • Pingyi Zhu,
  • Jianyi Qu,
  • Shunfa Huang,
  • Run Wang,
  • Jianjun Zhou,
  • Jianfeng Huang,
  • Chenchen Dai

摘要

Objective

To investigate the potential of multiparametric MRI clear cell likelihood scores (ccLS) for differentiating between fat-poor angiomyolipoma (AML) and clear cell renal cell carcinoma (ccRCC) in subcentimeter Lesions (1 cm or smaller).

Materials and methods

This retrospective study included consecutive patients with subcentimeter renal masses who underwent multiparametric MRI between September 2009 and September 2022 across three hospitals. Clinical and MRI findings were analyzed to differentiate between fat-poor AML and ccRCC. Lesions were categorized using the ccLS and receiver operating characteristic curve analysis was performed to assess ccLS performance.

Results

Thirty-eight patients (mean age: 52 years ± 12; 19 women) with 39 lesions were included. Of the 39 lesions [mean size: 9.1 mm ± 1.0 (range, 6.0–10.0 mm)], 20 (51%) were ccRCC and 19 (49%) were fat-poor AML. Compared to the ccRCC, subcentimeter fat-poor AMLs were more likely to show hypointensity on T2WI (P < 0.001), homogeneous enhancement (P = 0.010), the presence of microscopic fat (P = 0.036), and the absence of a pseudocapsule (P = 0.020). The diagnostic percentage of fat-poor AML was 47% for a ccLS of 1 or 2, and ccRCC accounted for 75% in the ccLS 4 or 5 category. The AUC for discrimination was 0.846 (95% CI: 0.695–0.941, P < 0.001), with a sensitivity of 75.00% (95% CI: 50.9–91.3) and a specificity of 89.47% (95% CI: 66.9–98.7).

Conclusion

Multiparametric MRI clear cell likelihood scores can potentially be used to differentiate between fat-poor AML and ccRCC in lesions 1 cm or smaller.