MARATTO

article · The Egyptian Journal of Radiology and Nuclear Medicine

Prospective evaluation of the diagnostic efficacy of multiparametric MRI clear cell Likelihood Score in small solid renal masses and its predictive value for tumor grade

2024Open accessMansoura University

Abstract

Abstract Background The detection of small renal masses has significantly increased due to the widespread use of cross-sectional imaging in recent years. Among these masses, clear cell renal cell carcinoma (ccRCC) is the most common subtype and progresses quickly, resulting in the advancement of the disease and the development of metastases. In this prospective study, our goal is to assess the effectiveness of multiparametric MRI clear cell Likelihood Score in small solid renal masses and its utility in predicting tumor grade. Results In total, 103 patients (mean age 52.5 ± 13.16 years) with small solid renal masses of stage T1a (≤ 4 cm) were identified. Mean tumor size was 3.4 ± 0.6 cm. According to our study results, the clear cell Likelihood Score (ccLS) had sensitivity of 75.6%, specificity of 93.5%, PPV of 88.6%, NPV of 85.3% and accuracy of 86.4% in diagnosing ccRCC using a ccLS threshold of 4 and 5. As regard the assessment of ccLS threshold of 1 or 2 in excluding ccRCC pathological subtype, our study found that out of 29 patients with ccLS 1 or 2, there was only 1 ccRCC case with false result (3% false positive). It was also noted that there is significant relation between Arterial-to-delayed-enhancement-ratio (ADER) value and the grade of the ccRCC. The median interquartile range (IQR) of ADER parameter was statistically significant higher in grade II compared to grade I (Median was 1.6 and 0.9 respectively) and much higher in grade III compared to grades I and II (Median was 2.9) with P value < 0.001. Conclusion This ccLS showed promising efficacy in prediction and exclusion of ccRCC subtype. Moreover, it aids in predicting the ccRCC grade.

Research topics

  • Renal cell carcinoma treatment
  • Renal and related cancers
  • MRI in cancer diagnosis

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.1186/s43055-024-01306-y

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.