Noninvasive Differentiation of Uric Acid versus Non-Uric Acid Kidney Stones Using Dual-Energy CT

Andrew N. Primak, Joel Garland Fletcher, Terri J Vrtiska, Oleksandr P. Dzyubak, John C Lieske, Molly E. Jackson, James C. Williams, Cynthia H McCollough

Research output: Contribution to journalArticle

253 Citations (Scopus)

Abstract

Rationale and Objectives: To determine the accuracy and sensitivity for dual-energy computed tomography (DECT) discrimination of uric acid (UA) stones from other (non-UA) renal stones in a commercially implemented product. Materials and Methods: Forty human renal stones comprising uric acid (n = 16), hydroxyapatite (n = 8), calcium oxalate (n = 8), and cystine (n = 8) were inserted in four porcine kidneys (10 each) and placed inside a 32-cm water tank anterior to a cadaver spine. Spiral dual-energy scans were obtained on a dual-source, 64-slice computed tomography (CT) system using a clinical protocol and automatic exposure control. Scanning was performed at two different collimations (0.6 mm and 1.2 mm) and within three phantom sizes (medium, large, and extra large) resulting in a total of six image datasets. These datasets were analyzed using the dual-energy software tool available on the CT system for both accuracy (number of stones correctly classified as either UA or non-UA) and sensitivity (for UA stones). Stone characterization was correlated with micro-CT. Results: For the medium and large phantom sizes, the DECT technique demonstrated 100% accuracy (40/40), regardless of collimation. For the extra large phantom size and the 0.6-mm collimation (resulting in the noisiest dataset), three (two cystine and one small UA) stones could not be classified (93% accuracy and 94% sensitivity). For the extra large phantom size and the 1.2-mm collimation, the dual-energy tool failed to identify two small UA stones (95% accuracy and 88% sensitivity). Conclusions: In an anthropomorphic phantom model, dual-energy CT can accurately discriminate uric acid stones from other stone types.

Original languageEnglish (US)
Pages (from-to)1441-1447
Number of pages7
JournalAcademic Radiology
Volume14
Issue number12
DOIs
StatePublished - Dec 2007

Fingerprint

Kidney Calculi
Uric Acid
Tomography
Acids
Cystine
Kidney
Calcium Oxalate
Durapatite
Clinical Protocols
Cadaver
Spine
Swine
Software
Water
Datasets

Keywords

  • dual-energy computed tomography
  • Kidney stones
  • renal calculi
  • uric acid
  • urolithiasis

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Noninvasive Differentiation of Uric Acid versus Non-Uric Acid Kidney Stones Using Dual-Energy CT. / Primak, Andrew N.; Fletcher, Joel Garland; Vrtiska, Terri J; Dzyubak, Oleksandr P.; Lieske, John C; Jackson, Molly E.; Williams, James C.; McCollough, Cynthia H.

In: Academic Radiology, Vol. 14, No. 12, 12.2007, p. 1441-1447.

Research output: Contribution to journalArticle

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abstract = "Rationale and Objectives: To determine the accuracy and sensitivity for dual-energy computed tomography (DECT) discrimination of uric acid (UA) stones from other (non-UA) renal stones in a commercially implemented product. Materials and Methods: Forty human renal stones comprising uric acid (n = 16), hydroxyapatite (n = 8), calcium oxalate (n = 8), and cystine (n = 8) were inserted in four porcine kidneys (10 each) and placed inside a 32-cm water tank anterior to a cadaver spine. Spiral dual-energy scans were obtained on a dual-source, 64-slice computed tomography (CT) system using a clinical protocol and automatic exposure control. Scanning was performed at two different collimations (0.6 mm and 1.2 mm) and within three phantom sizes (medium, large, and extra large) resulting in a total of six image datasets. These datasets were analyzed using the dual-energy software tool available on the CT system for both accuracy (number of stones correctly classified as either UA or non-UA) and sensitivity (for UA stones). Stone characterization was correlated with micro-CT. Results: For the medium and large phantom sizes, the DECT technique demonstrated 100{\%} accuracy (40/40), regardless of collimation. For the extra large phantom size and the 0.6-mm collimation (resulting in the noisiest dataset), three (two cystine and one small UA) stones could not be classified (93{\%} accuracy and 94{\%} sensitivity). For the extra large phantom size and the 1.2-mm collimation, the dual-energy tool failed to identify two small UA stones (95{\%} accuracy and 88{\%} sensitivity). Conclusions: In an anthropomorphic phantom model, dual-energy CT can accurately discriminate uric acid stones from other stone types.",
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AU - Dzyubak, Oleksandr P.

AU - Lieske, John C

AU - Jackson, Molly E.

AU - Williams, James C.

AU - McCollough, Cynthia H

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