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Hereditary Disease
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Magnetic Resonance Measurements of Renal Blood Flow and Disease Progression in Autosomal Dominant Polycystic Kidney Disease

Vicente E. Torres, Bernard F. King, Arlene B. Chapman, Marijn E. Brummer, Kyongtae T. Bae, James F. Glockner, Kraisthith Arya, Dana Risk, Joel P. Felmlee, Jared J. Grantham, Lisa M. Guay-Woodford, William M. Bennett, Saulo Klahr, Catherine M. Meyers, Xiaoling Zhang, Paul A. Thompson, J. Philip Miller and ; and the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP)
CJASN January 2007, 2 (1) 112-120; DOI: https://doi.org/10.2215/CJN.00910306
Vicente E. Torres
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Bernard F. King
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Arlene B. Chapman
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Marijn E. Brummer
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Kyongtae T. Bae
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James F. Glockner
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Kraisthith Arya
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Dana Risk
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Joel P. Felmlee
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Jared J. Grantham
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Lisa M. Guay-Woodford
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William M. Bennett
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Saulo Klahr
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Catherine M. Meyers
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Xiaoling Zhang
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Paul A. Thompson
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J. Philip Miller
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    Figure 1.

    Relationship among total kidney volume slopes and baseline log 10 kidney volumes, renal blood flows, iothalamate clearances, log 10 urine albumin excretions, serum uric acid levels, and urine sodium excretions.

  • Figure 2.
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    Figure 2.

    Relationship among iothalamate clearance slopes and baseline log 10 kidney volumes, iothalamate clearances, renal blood flows, and renal vascular resistances.

Tables

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    Table 1.

    Clinical, radiologic, and laboratory parametersa

    ParameterBaselineYear 1Year 2Year 3
    BMI25.67 ± 0.4525.93 ± 0.4426.08 ± 0.4526.41 ± 0.48c,d
    MAP (mmHg)96.3 ± 0.993.6 ± 0.9c92.5 ± 0.9c93.3 ± 1.1c
    Log 10 TKV (ml)2.95 ± 0.022.97 ± 0.02c3.00 ± 0.02c,d3.01 ± 0.02c,d,e
    Log 10 TCV (ml)2.50 ± 0.042.57 ± 0.04c2.61 ± 0.04c,d2.66 ± 0.04c,d,e
    RBF (ml/min per 1.73 m2)b736.8 ± 20.2683.6 ± 16.0c644.4 ± 17.7c,d602.6 ± 23.0c,d,e
    RVR (dynes s/cm−5)b11,552 ± 36811,788 ± 33912,606 ± 414c,d13,391 ± 588c,d
    GFR (ml/min per 1.73 m2)98.7 ± 2.098.7 ± 2.199.2 ± 2.495.9 ± 2.4
    RPF (ml/min per 1.73 m2)b446.5 ± 12.0419.8 ± 9.2c394.2 ± 11.0c,d359.8 ± 13.4c,d
    Log 10 FF (%)b−0.648 ± 0.010−0.633 ± 0.010−0.598 ± 0.012c,d−0.575 ± 0.012c,d
    Serum creatinine (mg/dl)1.00 ± 0.020.99 ± 0.021.01 ± 0.021.04 ± 0.02c,d,e
    MDRD GFR85.2 ± 2.2484.8 ± 2.083.4 ± 2.279.9 ± 2.0c,d,e
    Serum uric acid (mg/dl)5.02 ± 0.125.01 ± 0.125.19 ± 0.13c,d5.38 ± 0.14c,d,e
    Serum HDL cholesterol (mg/dl)47.8 ± 1.142.7 ± 1.0c42.7 ± 1.0c42.7 ± 1.1c
    Serum LDL cholesterol (mg/dl)101.2 ± 2.8100.1 ± 2.1100.0 ± 2.5100.0 ± 2.6
    Urine volume (ml/d)2427 ± 962797 ± 90c2730 ± 95c2768 ± 99c
    UNaE (mEq/d)182.3 ± 6.9190.0 ± 6.7190.2 ± 6.7181.3 ± 6.3
    Log 10 UAE (mg/d)1.38 ± 0.041.34 ± 0.041.36 ± 0.041.45 ± 0.05d,e
    Protein intake (g/d)71.7 ± 2.072.9 ± 2.175.7 ± 2.0c75.6 ± 2.1c
    • ↵a Data are means ± SEM. BMI, body mass index; FF, filtration fraction; MAP, mean arterial pressure; MDRD, Modification of Diet in Renal Disease; RBF, renal blood flow; RPF, renal plasma flow; RVR, renal vascular resistance; TKC, total cyst volume; TKV, total kidney volume; UAE, urinary albumin excretion; UNaE, urinary sodium excretion.

    • ↵b Year 3 RBF, RPF, FF, and RVR values and statistical comparisons with baseline, year 1, and year 2 include only patients who were studied at the Mayo Clinic.

    • P < 0.05 versus

    • ↵c baseline,

    • ↵d year 1, and

    • ↵e year 2 values.

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    Table 2.

    Pearson correlation coefficients among baseline clinical, radiologic, or laboratory parameters and the slopes of log 10 TKV, log 10 TCV, measured GFR or estimated MDRD GFR

    ParameterLog 10 TKV SlopeLog 10 TCV SlopeGFR SlopeMDRD GFR Slope
    rPrPrPrP
    Age0.220.0180.250.006−0.08NS0.14NS
    BMI0.190.0420.17NS−0.05NS0.300.001
    MAP0.180.0530.210.021−0.240.010−0.08NS
    Log 10 TKV0.69<0.0010.73<0.001−0.40<0.001−0.05NS
    Log 10 TCV0.64<0.0010.65<0.001−0.38<0.001−0.06NS
    GFR−0.180.052−0.17NS−0.280.002−0.08NS
    RBF−0.30<0.001−0.33<0.0010.240.0090.15NS
    RVR0.37<0.0010.41<0.001−0.300.001−0.13NS
    MDRD GFR−0.260.004−0.250.0060.06NS−0.39<0.001
    Serum uric acid0.34<0.0010.33<0.001−0.07NS0.13NS
    Serum HDL cholesterol−0.180.051−0.14NS−0.06NS−0.200.028
    Serum LDL cholesterol0.09NS0.04NS−0.09NS0.12NS
    Urine volume0.17NS0.14NS−0.04NS0.07NS
    UNaE0.300.0010.260.005−0.05NS0.08NS
    UAE0.33<0.0010.310.001−0.01NS−0.10NS
    Protein intake0.16NS0.14NS−0.01NS0.200.027
    • View popup
    Table 3.

    Regression model predicting structural disease progression (TKV) from baseline parameters

    ParameterTKV Slope (R2; ml/yr)
    0.580.40
    baSEPbaSEP
    Male gender1.014.3NS−8.017.0NS
    Age (yr)−0.580.68NS0.690.78NS
    BMI0.141.04NS0.411.23NS
    Hypertension2.810.9NS22.112.5NS
    MAP (mmHg)−0.590.46NS−0.280.54NS
    Log 10 TKV (ml)16825<0.001———
    GFR (ml/min per 1.73 m2)0.350.25NS0.350.29NS
    RBF (ml/min per 1.73 m2)−0.060.030.038−0.090.030.004
    Serum uric acid (mg/dl)4.565.49NS7.976.51NS
    Serum HDL cholesterol (mg/dl)−0.510.47NS−0.670.56NS
    Serum LDL cholesterol (mg/dl)0.120.14NS0.110.17NS
    Urine volume (L)2.404.74NS0.65.6NS
    UNaE (mEq/24 h)0.180.080.0230.260.090.005
    Log 10 UAE (mg/24 h)12.211.9NS46.712.8<0.001
    Protein intake (g/24 h)−0.220.29NS−0.070.34NS
    • ↵a Slopes per unit change in baseline parameters. For example, a lower baseline RBF by 100 ml/min per 1.73 m2 predicts a steeper increase in the slope of TKV by 6 (with TKV included as a regressor) or 9 ml/yr (without TKV included as a regressor).

    • View popup
    Table 4.

    Regression models predicting functional disease progression (GFR) from baseline parameters

    ParameterGFR Slope (R2; ml/min per 1.73 m2 per yr)
    0.550.28
    baSEPbaSEP
    Male gender0.802.17NS0.862.71NS
    Age (yr)0.090.10NS0.290.120.021
    BMI0.180.16NS0.120.20NS
    Hypertension−0.621.65NS−0.832.06NS
    MAP (mmHg)−0.070.07NS−0.120.09NS
    Log 10 TKV (mL)−20.83.9<0.001−20.84.8<0.001
    GFR (ml/min per 1.73 m2)−0.280.04<0.001———
    RBF (ml/min per 1.73 m2)0.020.00<0.0010.010.00NS
    Serum uric acid (mg/dl)−0.670.83NS0.381.02NS
    Serum HDL cholesterol (mg/dl)−0.050.07NS−0.080.09NS
    Serum LDL cholesterol (mg/dl)−0.030.02NS−0.040.03NS
    Urine volume (L)−0.350.72NS0.170.89NS
    UNaE (mEq/24 h)−0.000.01NS−0.010.01NS
    Log 10 UAE (mg/24 h)5.071.810.0065.842.250.011
    Protein intake (g/24 h)0.030.04NS0.020.05NS
    • ↵a Slopes per unit change in baseline parameters.

    • View popup
    Table 5.

    Regression model predicting RBF slopes from parameters at baseline or averaged during the whole period of observation (baseline through year 3)

    ParameterRBF Slope (R2; ml/min per 1.73 m2 per yr)
    0.220.20
    baSEPbbSEP
    Male gender−22.224.2NS−28.724.9NS
    Age (yr)1.391.14NS1.561.21NS
    BMI1.381.75NS0.051.88NS
    Hypertension−40.318.30.030−34.318.3NS
    MAP (mmHg)1.120.77NS1.181.00NS
    Log 10 TKV (ml)−27.942.3NS−68.052.3NS
    GFR (ml/min per 1.73 m2)−0.0.560.38NS−0.620.47NS
    Serum uric acid (mg/dl)20.39.10.02717.59.4NS
    Serum HDL cholesterol (mg/dl)1.640.750.0312.110850.015
    Serum LDL cholesterol (mg/dl)−0.390.24NS−0.280.31NS
    Urine volume (L)−7.38.0NS−12.88.7NS
    UNaE (mEq/24 h)−0.150.13NS−0.100.19NS
    Log 10 UAE (mg/24 h)38.020.2NS46.329.4NS
    Protein intake (g/24 h)0.410.47NS0.810.69NS
    • ↵a Slopes per unit change in baseline parameters.

    • ↵b Slopes per unit change averaged during the whole period of observation.

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Clinical Journal of the American Society of Nephrology
Vol. 2, Issue 1
January 2007
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Magnetic Resonance Measurements of Renal Blood Flow and Disease Progression in Autosomal Dominant Polycystic Kidney Disease
Vicente E. Torres, Bernard F. King, Arlene B. Chapman, Marijn E. Brummer, Kyongtae T. Bae, James F. Glockner, Kraisthith Arya, Dana Risk, Joel P. Felmlee, Jared J. Grantham, Lisa M. Guay-Woodford, William M. Bennett, Saulo Klahr, Catherine M. Meyers, Xiaoling Zhang, Paul A. Thompson, J. Philip Miller
CJASN Jan 2007, 2 (1) 112-120; DOI: 10.2215/CJN.00910306

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Magnetic Resonance Measurements of Renal Blood Flow and Disease Progression in Autosomal Dominant Polycystic Kidney Disease
Vicente E. Torres, Bernard F. King, Arlene B. Chapman, Marijn E. Brummer, Kyongtae T. Bae, James F. Glockner, Kraisthith Arya, Dana Risk, Joel P. Felmlee, Jared J. Grantham, Lisa M. Guay-Woodford, William M. Bennett, Saulo Klahr, Catherine M. Meyers, Xiaoling Zhang, Paul A. Thompson, J. Philip Miller
CJASN Jan 2007, 2 (1) 112-120; DOI: 10.2215/CJN.00910306
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