>MRI/CT-calculated Total Kidney Volume

MRI/CT-calculated Total Kidney Volume

Total kidney volume (TKV) is a strong predictor of future renal insufficiency in ADPKD.¹ Various imaging modalities (MRI, CT, US) and post processing methods (stereology and ellipsoid calculations) are available to determine TKV.^1,2

Once TKV has been calculated, it can be used to assess the risk of ADPKD progression in Typical (Class 1) patients, more specifically by estimating TKV growth and eGFR decline over time. This method can be useful in assessing younger patients who may still have normal eGFR levels.^2,3

For Atypical (class 2) patients, ADPKD progression should be classified using an expanded imaging classification model which employs a recalculated htTKV measure that excludes prominent exophytic cysts to improve prediction for eGFR decline.⁴

View a hypothetical patient sample calculation or enter practice values to
learn how to measure TKV to assess disease progression:

Patient A (29)height 1.85 m Patient B (45)height 1.70 m Enter Practice Values

How to Measure TKV using MRI or CT images and the ellipsoid volume equation

Determining TKV by stereology can be time-consuming and depends on specialized software that is not available to all clinicians. Estimation of TKV by the ellipsoid volume equation (shown below) requires only a few minutes and has sufficient precision to substitute stereology in the classification assignment.^2,3

The ellipsoid volume equation uses length, width, and depth measurements determined from the sagittal, coronal and transverse views of an MRI or CT scan.*^3,5

Sagittal View

Coronal View

Transverse View

* Imaging services such as MRI or CT may not be available in all cases. Radiologists may take a different approach than the example provided to determine kidney length, width and depth measurements from MRI or CT scans.

Enter kidney dimensions:

Left Kidney

Length* (mm)Width^† (mm)Depth^† (mm)

Right Kidney

*Length. The length can be obtained by averaging the maximum longitudinal diameters taken from coronal and sagittal images. Alternatively, a single, longitudinal diameter measurement can be obtained from a tilted coronal image.^3,4

^†Width and depth. Use the width and depth of the kidney obtained from transverse images at the maximum transverse diameter.³

Start with the
basic formula:

•

Left Kidney( L_LxW_LxD_L )

•

Right Kidney( L_RxW_RxD_R )

= TKV

How to Use TKV to Assess Risk for ADPKD Progression

With height-adjusted TKV (htTKV), you can see your classification for annual kidney growth and risk for eGFR decline.³

Start with the
basic formula:

TKVheight

= htTKV

ADPKD Imaging Classification by htTKV and Age*

Patient Classifications*

1E>6%High Risk

1D4.5% - 6%High Risk

1C3% - 4.5%High Risk

1B1.5% - 3%Intermediate Risk

1A<1.5%Low Risk

Adapted with permission of The American Society of Nephrology, from Irazabal MV, et al. Imaging classification of autosomal polycystic kidney disease: a simple model for selecting patients for clinical trials. J Am Soc Nephrol. 2015;26(1):160-172.

Reset

*Classification is a simple model for selecting patients for clinical trials.

ADPKD=autosomal dominant polycystic kidney disease; TKV=total kidney volume; MRI=magnetic resonance imaging; CT=computed tomography; US=ultrasound; eGFR=estimated glomerular filtration rate; htTKV=height-adjusted total kidney volume.

References:

1. Bhutani H, et al. A comparison of ultrasound and magnetic resonance imaging shows that kidney length predicts chronic kidney disease in autosomal dominant polycystic kidney disease. Kidney Int. 2015;88:146-151.

2. Soroka S, et al. Assessing risk of disease progression and pharmacological management of autosomal dominant kidney disease: a Canadian expert consensus. Can J Kidney Health Dis. 2017;4:1-12.

3. Irazabal MV, et al. Imaging classification of autosomal dominant polycystic kidney disease: a simple model for selecting patients for clinical trials. J Am Soc Nephrol. 2015;26:160-172.

4. Bae, K.T. et al. Expanded imaging classification of autosomal dominant polycystic kidney disease. Journal of the American Society of Nephrology. 2020; 31(7), pp.1640-1651

5. Higashihara E, et al. Kidney volume estimations with ellipsoid equations by magnetic resonance imaging in autosomal dominant polycystic kidney disease. Nephron. 2015;129:253-262.

6. Imaging classification of ADPKD: a simple model for selecting patients for clinical trials. http://www.mayo.edu/research/documents/pkd-center-adpkd-classification/doc-20094754. Accessed: January 09, 2019.

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