Ultrasound detection and characterization of polycystic kidney disease in a mouse model

Rachel Pollard, Reem Yunis, Dietmar Kültz, Phillip Martin, Stephen Griffey, Katherine W Ferrara

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


We sought to use ultrasonography to quantify renal size and echogenicity in a mouse model of polycystic kidney disease. We imaged 36 wild-type (WT) and juvenile cystic kidney (jck) mice by using a standard ultrasound unit and 10-5 MHz linear transducer. Mice were imaged at 3 (6 WT, 7 jck), 6 (7 WT, 5 jck), and 9 (6 WT, 5 jck) wk of age. Kidney length, width, and height were recorded for volume calculation. Sagittal images of both kidneys were recorded for assessment of intensity. Quantitative values were obtained from areas of similar depth and gain settings. Kidney and liver intensities were determined for calculation of their ratio. Representative histologic kidney sections were stained with hematoxylin and eosin and digitized for calculation of cyst number, mean cyst area, and percentage cystic area. We found that renal volume was greater in jck than WT mice at 3 (P < 0.0001), 6 (P < 0.0001), and 9 (P < 0.0001) wk of age. In addition, kidney intensity and kidney:liver ratio were higher in jck than WT mice at 3 (P < 0.002 for both parameters), 6 (P < 0.04), and 9 wk (P < 0.008). Kidneys with smaller mean cyst size and less percentage cystic space had higher intensity values. We therefore conclude that ultrasound measures of renal volume and intensity can noninvasively identify jck-affected mice as early as 3 wk of age. Cortical intensity is greater in jck versus WT mice and appears affected by percentage cyst area and mean cyst size.

Original languageEnglish (US)
Pages (from-to)215-221
Number of pages7
JournalComparative Medicine
Issue number3
StatePublished - Jun 2006

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)


Dive into the research topics of 'Ultrasound detection and characterization of polycystic kidney disease in a mouse model'. Together they form a unique fingerprint.

Cite this