Rationale and Objectives
Total kidney volume is an important biomarker for the evaluation of autosomal dominant polycystic kidney disease progression. In this study, we present a novel approach for automated segmentation of polycystic kidneys from non–contrast-enhanced computed tomography (CT) images.
Materials and Methods
Non–contrast-enhanced CT images were acquired from 21 patients with a diagnosis of autosomal dominant polycystic kidney disease. Kidney volumes obtained from the fully automated method were compared to volumes obtained by manual segmentation and evaluated using linear regression and Bland-Altman analyses. Dice coefficient was used for performance evaluation.
Results
Kidney volumes from the automated method well correlated with the ones obtained by manual segmentation. Bland-Altman analysis showed a low percentage bias (−0.3%) and narrow limits of agreements (11.0%). The overlap between the three-dimensional kidney surfaces obtained with our approach and by manual tracing, expressed in terms of Dice coefficient, showed good agreement (0.91 ± 0.02).
Conclusions
This preliminary study showed the proposed fully automated method for renal volume assessment is feasible, exhibiting how a correct use of biomedical image processing may allow polycystic kidney segmentation also in non–contrast-enhanced CT. Further investigation on a larger dataset is needed to confirm the robustness of the presented approach.
Introduction
Autosomal dominant polycystic kidney disease (ADPKD) is an inherited disorder that is characterized by the development and growth of cysts in both kidneys. Despite a progressive enlargement of the kidneys as a consequence of cyst expansion, especially at the first stages of the disease, the renal function is still preserved. For this reason, common renal function parameters such as the glomerular filtration rate are inadequate for the evaluation of disease progression. Nowadays, total kidney volume (TKV) is considered as the most important biomarker of disease progression and is widely used in clinical trials for the evaluation of the efficacy of new pharmacologic therapies .
The Consortium for Radiological Imaging Studies of Polycystic Kidney Disease (CRISP) recommends the use of three-dimensional (3D) imaging for an accurate and reproducible assessment of TKV. Both magnetic resonance imaging (MRI) and computed tomography (CT) provide reliable measurements of TKV . CT may require the use of a potentially nephrotoxic contrast medium and exposes the patient to ionizing radiation. However, CT imaging systems are widely available with respect to MRI systems, also in small centers, and CT imaging is straightforward and fast.
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Materials and Methods
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Table 1
Patient Characteristics
Characteristic Value Number of patients 21 Sex (M/F) 12/9 Age at visit (y), mean ± SD (range) 46 ± 17 (18–77) Total kidney volume (mL), median (range) 951 (239–4853) Left kidney volume (mL), median (range) 592 (117–2182) Right kidney volume (mL), median (range) 426 (123–2671)
F, female; M, male; SD, standard deviation.
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Image Analysis
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Results
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Discussion and Conclusion
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