Work overview

Section 05 of 10

CT

Integrating kidney imaging for risk prediction, therapeutic monitoring, and prognostication across the kidney disease spectrum: a review of emerging evidence

Mustafa Guldan, Ibrahim Gulmaliyev, Rama AlShiab, Ermeena Shah, Lasin Ozbek, Mahmut Altindal, Bengi Gurses, Magdalena Madero, Alberto Ortiz, Adrian Covic, and Mehmet Kanbay · 2026

Contents

Section 05 of 10

  1. 01INTRODUCTION
  2. 02IMAGING IN EARLY RENAL INJURY
  3. 03US-BASED IMAGING
  4. 04MRI TECHNIQUES
  5. 05CT
  6. 06MORE ON SPECIFIC CASE-USE IN KIDNEY DISEASE: FATTY KIDNEY AND KIDNEY TRANSPLANTATION
  7. 07INTEGRATION OF AI AND RADIOMICS IN GENERAL NEPHROLOGY AND KIDNEY TRANSPLANTATION
  8. 08FUTURE DIRECTIONS AND RESEARCH GAPS
  9. 09ONGOING TRIALS
  10. 10CONCLUSION
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Work overview

Section 5 of 10

CT

Mustafa Guldan, Ibrahim Gulmaliyev, Rama AlShiab, Ermeena Shah, Lasin Ozbek, Mahmut Altindal, Bengi Gurses, Magdalena Madero, Alberto Ortiz, Adrian Covic, and Mehmet Kanbay · about 1 minutes

Original source ↗

For quantification of the renal-sinus fat volume, non-contrast multidetector computed tomography remains the cornerstone imaging modality. A validation study of 98 out–patients in 2024 showed that a single anteroposterior diameter of the renal sinus (APDRS) correlates strongly with volumetric region-scalable fitting (RSF) segmentation (r = 0.80) and is highly reproducible [inter–reader intraclass correlation coefficient (ICC) = 0.98] [48]. Similarly, single-slice right-kidney protocols have shown to have high intra-reader ICC (0.93) and inter-reader ICC (0.86) reproducibility [49].