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Purpose <p>To evaluate the prognostic significance of computed tomography (CT)-based radiomic features of urinary stones in predicting stone-free rate (SFR) after extracorporeal shockwave lithotripsy (ESWL) and laser lithotripsy.</p> Methods <p>A systematic literature search of several databases using Boolean operators was performed according to PRISMA guideline and registered in PROSPERO (CRD420250650566). Studies using CT-based radiomics to predict SFR after ESWL or laser lithotripsy and reporting area under the receiver operating characteristic curve (AUC) with 95% confidence intervals (CI) were included. CLAIM and PROBAST checklists were used to assess transparency and and and risk of bias, respectively. A random-effects meta-analysis was performed to pool AUC estimates and assess heterogeneity.</p> Results <p>Seven studies were selected and analyzed, of which five described radiomic prediction for ESWL and were analyzed in the meta-analysis. The pooled AUC for radiomics-based models predicting SFR after ESWL was 0.883 (95% CI: 0.840–0.927), with low heterogeneity (I<sup>2</sup> = 24.3%) and a prediction interval of 0.77–0.96. All studies were rated at high risk of bias with moderate compliance.</p> Conclusion <p>Adding CT-based radiomic features of stones to other clinical and radiologic parameters can predict SFR after ESWL with an AUC of &gt; 0.85. However, the results are based on a small number of studies mostly with a high risk of bias, so follow-up studies performed according to the tenets of using radiomic analysis are needed.</p>

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CT-based radiomics for predicting stone-free rate after ESWL: a systematic review and meta-analysis

  • 期刊论文

  • 发表日期：

    2025年9月20日

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  • Ali Talyshinskii,
  • Stanislav Ali,
  • Vineet Gauhar,
  • Selcuk Güven,
  • Bhaskar Kumar Somani,
  • Kemal Sarica,
  • Nariman Gadzhiev

摘要

Purpose

To evaluate the prognostic significance of computed tomography (CT)-based radiomic features of urinary stones in predicting stone-free rate (SFR) after extracorporeal shockwave lithotripsy (ESWL) and laser lithotripsy.

Methods

A systematic literature search of several databases using Boolean operators was performed according to PRISMA guideline and registered in PROSPERO (CRD420250650566). Studies using CT-based radiomics to predict SFR after ESWL or laser lithotripsy and reporting area under the receiver operating characteristic curve (AUC) with 95% confidence intervals (CI) were included. CLAIM and PROBAST checklists were used to assess transparency and and and risk of bias, respectively. A random-effects meta-analysis was performed to pool AUC estimates and assess heterogeneity.

Results

Seven studies were selected and analyzed, of which five described radiomic prediction for ESWL and were analyzed in the meta-analysis. The pooled AUC for radiomics-based models predicting SFR after ESWL was 0.883 (95% CI: 0.840–0.927), with low heterogeneity (I2 = 24.3%) and a prediction interval of 0.77–0.96. All studies were rated at high risk of bias with moderate compliance.

Conclusion

Adding CT-based radiomic features of stones to other clinical and radiologic parameters can predict SFR after ESWL with an AUC of > 0.85. However, the results are based on a small number of studies mostly with a high risk of bias, so follow-up studies performed according to the tenets of using radiomic analysis are needed.