Screening for transplant renal artery stenosis: Ultrasound-based stenosis probability stratifcation

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Abstract

OBJECTIVE. The objective of our study was to evaluate which spectral Doppler ultrasound parameters are useful in patients with clinical concern for transplant renal artery stenosis (TRAS) and create mathematically derived prediction models that are based on these parameters. MATERIALS AND METHODS. The study subjects included 120 patients with clinical signs of renal dysfunction who had undergone ultrasound followed by angiography (either digital subtraction angiography or MR angiography) between January 2005 and December 2015. Five ultrasound variables were evaluated: ratio of highest renal artery velocity to iliac artery velocity, highest renal artery velocity, spectral broadening, resistive indexes, and acceleration time. Angiographic studies were categorized as either showing no stenosis or showing stenosis. Reviewers assessed the ultrasound examinations for TRAS using all fve variables, which we refer to as the full model, and using a reduced number of variables, which we refer to as the reduced-variable model; sensitivities and specifcities were generated. RESULTS. Ninety-seven patients had stenosis and 23 had no stenosis. The full model had a sensitivity and specifcity of 97% and 91%, respectively. The reduced-variable model excluded the ratio and resistive index variables without affecting sensitivity and specifcity. We applied cutoff values to the variables in the reduced-variable model, which we refer to as the simple model. Using these cutoff values, the simple model showed a sensitivity and specifcity of 96% and 83%. The simple model was able to categorize patients into four risk categories for TRAS: low, intermediate, high, and very high risk. CONCLUSION. We propose a simple model that is based on highest renal artery velocity, distal spectral broadening, and acceleration time to classify patients into risk categories for TRAS.

Original languageEnglish (US)
Pages (from-to)1064-1073
Number of pages10
JournalAmerican Journal of Roentgenology
Volume209
Issue number5
DOIs
StatePublished - Nov 1 2017

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Renal Artery Obstruction
Pathologic Constriction
Transplants
Renal Artery
Angiography
Doppler Ultrasonography
Digital Subtraction Angiography
Iliac Artery
Kidney

Keywords

  • Kidney
  • Renal artery stenosis
  • Renal graft
  • Transplant

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

@article{15d89db620904e11bc08a40fd6fb41ad,
title = "Screening for transplant renal artery stenosis: Ultrasound-based stenosis probability stratifcation",
abstract = "OBJECTIVE. The objective of our study was to evaluate which spectral Doppler ultrasound parameters are useful in patients with clinical concern for transplant renal artery stenosis (TRAS) and create mathematically derived prediction models that are based on these parameters. MATERIALS AND METHODS. The study subjects included 120 patients with clinical signs of renal dysfunction who had undergone ultrasound followed by angiography (either digital subtraction angiography or MR angiography) between January 2005 and December 2015. Five ultrasound variables were evaluated: ratio of highest renal artery velocity to iliac artery velocity, highest renal artery velocity, spectral broadening, resistive indexes, and acceleration time. Angiographic studies were categorized as either showing no stenosis or showing stenosis. Reviewers assessed the ultrasound examinations for TRAS using all fve variables, which we refer to as the full model, and using a reduced number of variables, which we refer to as the reduced-variable model; sensitivities and specifcities were generated. RESULTS. Ninety-seven patients had stenosis and 23 had no stenosis. The full model had a sensitivity and specifcity of 97{\%} and 91{\%}, respectively. The reduced-variable model excluded the ratio and resistive index variables without affecting sensitivity and specifcity. We applied cutoff values to the variables in the reduced-variable model, which we refer to as the simple model. Using these cutoff values, the simple model showed a sensitivity and specifcity of 96{\%} and 83{\%}. The simple model was able to categorize patients into four risk categories for TRAS: low, intermediate, high, and very high risk. CONCLUSION. We propose a simple model that is based on highest renal artery velocity, distal spectral broadening, and acceleration time to classify patients into risk categories for TRAS.",
keywords = "Kidney, Renal artery stenosis, Renal graft, Transplant",
author = "Ghaneh Fananapazir and McGahan, {John P} and Corwin, {Michael T} and Stewart, {Susan L} and Vu, {Catherine T} and Luke Wright and Christoph Troppmann",
year = "2017",
month = "11",
day = "1",
doi = "10.2214/AJR.17.17913",
language = "English (US)",
volume = "209",
pages = "1064--1073",
journal = "American Journal of Roentgenology",
issn = "0361-803X",
publisher = "American Roentgen Ray Society",
number = "5",

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TY - JOUR

T1 - Screening for transplant renal artery stenosis

T2 - Ultrasound-based stenosis probability stratifcation

AU - Fananapazir, Ghaneh

AU - McGahan, John P

AU - Corwin, Michael T

AU - Stewart, Susan L

AU - Vu, Catherine T

AU - Wright, Luke

AU - Troppmann, Christoph

PY - 2017/11/1

Y1 - 2017/11/1

N2 - OBJECTIVE. The objective of our study was to evaluate which spectral Doppler ultrasound parameters are useful in patients with clinical concern for transplant renal artery stenosis (TRAS) and create mathematically derived prediction models that are based on these parameters. MATERIALS AND METHODS. The study subjects included 120 patients with clinical signs of renal dysfunction who had undergone ultrasound followed by angiography (either digital subtraction angiography or MR angiography) between January 2005 and December 2015. Five ultrasound variables were evaluated: ratio of highest renal artery velocity to iliac artery velocity, highest renal artery velocity, spectral broadening, resistive indexes, and acceleration time. Angiographic studies were categorized as either showing no stenosis or showing stenosis. Reviewers assessed the ultrasound examinations for TRAS using all fve variables, which we refer to as the full model, and using a reduced number of variables, which we refer to as the reduced-variable model; sensitivities and specifcities were generated. RESULTS. Ninety-seven patients had stenosis and 23 had no stenosis. The full model had a sensitivity and specifcity of 97% and 91%, respectively. The reduced-variable model excluded the ratio and resistive index variables without affecting sensitivity and specifcity. We applied cutoff values to the variables in the reduced-variable model, which we refer to as the simple model. Using these cutoff values, the simple model showed a sensitivity and specifcity of 96% and 83%. The simple model was able to categorize patients into four risk categories for TRAS: low, intermediate, high, and very high risk. CONCLUSION. We propose a simple model that is based on highest renal artery velocity, distal spectral broadening, and acceleration time to classify patients into risk categories for TRAS.

AB - OBJECTIVE. The objective of our study was to evaluate which spectral Doppler ultrasound parameters are useful in patients with clinical concern for transplant renal artery stenosis (TRAS) and create mathematically derived prediction models that are based on these parameters. MATERIALS AND METHODS. The study subjects included 120 patients with clinical signs of renal dysfunction who had undergone ultrasound followed by angiography (either digital subtraction angiography or MR angiography) between January 2005 and December 2015. Five ultrasound variables were evaluated: ratio of highest renal artery velocity to iliac artery velocity, highest renal artery velocity, spectral broadening, resistive indexes, and acceleration time. Angiographic studies were categorized as either showing no stenosis or showing stenosis. Reviewers assessed the ultrasound examinations for TRAS using all fve variables, which we refer to as the full model, and using a reduced number of variables, which we refer to as the reduced-variable model; sensitivities and specifcities were generated. RESULTS. Ninety-seven patients had stenosis and 23 had no stenosis. The full model had a sensitivity and specifcity of 97% and 91%, respectively. The reduced-variable model excluded the ratio and resistive index variables without affecting sensitivity and specifcity. We applied cutoff values to the variables in the reduced-variable model, which we refer to as the simple model. Using these cutoff values, the simple model showed a sensitivity and specifcity of 96% and 83%. The simple model was able to categorize patients into four risk categories for TRAS: low, intermediate, high, and very high risk. CONCLUSION. We propose a simple model that is based on highest renal artery velocity, distal spectral broadening, and acceleration time to classify patients into risk categories for TRAS.

KW - Kidney

KW - Renal artery stenosis

KW - Renal graft

KW - Transplant

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JO - American Journal of Roentgenology

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