Quantitative Evaluation of Chronically Obstructed Kidneys fr
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The U-Net model can measure and report the renal parenchymal volume (RPV), renal sinus volume (RSV), and renal parenchymal density (RPD) of chronically obstructed kidneys with high efficiency and reliability. Smaller RPV, larger RSV, and older age were associated with lower split glomerular filtration rate (sGFR) in chronically obstructed kidneys, and the RPD was slightly increased in kidneys with severe dysfunction. Quantitative measurements based on non-contrast computed tomography (NCCT) show potential for becoming a single radiological procedure for morphological and functional evaluation of chronically obstructed kidneys.

The study published in the European Journal of Radiology was aimed to quantitatively report renal parenchymal volume (RPV), renal sinus volume (RSV), and renal parenchymal density (RPD) for chronically obstructed kidneys from non-contrast computed tomography (NCCT).

The researchers retrospectively collected 304 consecutive NCCT scans of urinary obstruction and constructed two datasets: one with 167 patient scans for parenchyma and sinus segmentation (segmentation dataset) and the other containing 137 scans from different patients diagnosed with chronic urinary obstruction (CUO dataset) and paired with split glomerular filtration rate (sGFR). A cascaded three-dimensional (3D) U-Net model was developed and validated for parenchyma and sinus segmentation. The RPV, RSV, and RPD of the CUO dataset were calculated by the model with manual editing. A multivariate analysis was performed to show the association between all parameters and the sGFR.

Compared with those of nonobstructed kidneys, the RSV and RPD of obstructed kidneys increased, but RPV and sGFR decreased. For chronically obstructed kidneys, age, RPV, RSV, and RPD were significantly correlated with sGFR.

Conclusively, NCCT combined with deep learning has the potential to be a single radiological procedure for morphological and functional evaluation of chronically obstructed kidneys.

Source: https://doi.org/10.1016/j.ejrad.2021.109535
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