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Evaluation of pediatric hydronephrosis using deep learning quantification of fluid-to-kidney-area ratio by ultrasonography

  • Kidneys, Ureters, Bladder, Retroperitoneum
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

Hydronephrosis is the dilation of the pelvicalyceal system due to the urine flow obstruction in one or both kidneys. Conventionally, renal pelvis anterior–posterior diameter (APD) was used for quantifying hydronephrosis in medical images (e.g., ultrasound, CT, and functional MRI). Our study aimed to automatically detect and quantify the fluid and kidney areas on ultrasonography, using a deep learning approach.

Methods

An attention-Unet was used to segment the kidney and the dilated pelvicalyceal system with fluid. The gold standard for diagnosing hydronephrosis was the APD > 1.0 cm. For semi-quantification, we proposed a fluid-to-kidney-area ratio measurement, i.e., \(\frac{{{\text{renal~pelvicalyceal~area~with~fluid}}}}{{{\text{~kidney~area}}}}\), as a deep learning-derived biomarker. Dice coefficient, confusion matrix, ROC curve, and Z-test were used to evaluate the model performance. Linear regression was applied to obtain the fluid-to-kidney-area ratio cutoff for detecting hydronephrosis.

Results

For regional kidney segmentation, the Dice coefficients were 0.92 and 0.83 for the kidney and dilated pelvicalyceal system, respectively. The sensitivity and specificity of detecting dilated pelvicalyceal system were 0.99 and 0.83, respectively. The linear equation was fluid-to-kidney-area ratio = (0.213 ± 0.004) × APD (in cm) for 95% confidence interval on the slope with R2 = 0.87. The fluid-to-kidney-area ratio cutoff for detecting hydronephrosis was 0.213. The sensitivity and specificity for detecting hydronephrosis were 0.90 and 0.80, respectively.

Conclusion

Our study confirmed the feasibility of deep learning characterization of the kidney and fluid, showing an automatic pediatric hydronephrosis detection.

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Abbreviations

APD:

Anterior–posterior diameter

UTI:

Urinary tract infection

CAP:

Continuous antibiotic prophylaxis

CKD:

Chronic kidney disease

SFU:

Society for fetal urology

UTD:

Urinary tract dilation

SAM:

Active shape models

AUC:

Area under the curve

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Authors and Affiliations

  1. Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong SAR, China

    Yingying Lin, Pek-Lan Khong & Peng Cao

  2. Ultrasound Department, Shenzhen Maternity and Child Health Care Hospital, Shengzhen, China

    Zhiying Zou

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Correspondence to Peng Cao.

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Lin, Y., Khong, PL., Zou, Z. et al. Evaluation of pediatric hydronephrosis using deep learning quantification of fluid-to-kidney-area ratio by ultrasonography. Abdom Radiol 46, 5229–5239 (2021). https://doi.org/10.1007/s00261-021-03201-w

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