Rationale and Objectives
To assess whether dual-energy computed tomography (DECT) multidetector computed tomography (MDCT) angiography improves vascular contrast beyond MDCT angiography and digital subtraction angiography (DSA) while preserving the ability to precisely characterize stenoses, using DSA as reference standard.
Materials and Methods
This prospective, Health Insurance Portability and Accountability Act–compliant, institutional review board–approved study was performed on 25 patients referred for lower extremity DECT angiography and subsequent DSA. Spectral data were postprocessed to create single-energy 120 kVp (MDCT series) and iodine-only (DECT series) datasets. The arterial tree was subdivided into 11 anatomical levels. Contrast-to-noise ratios (CNR) and corresponding coefficient -of variation (CV) of patent vessel segments were evaluated for DECT, MDCT, and DSA using analysis of variance comparisons. Degree of stenoses was determined for DECT, MDCT, and DSA and correlated with t -test, bivariate Pearson comparisons, and Bland-Altman plots.
Results
Patent vasculature comprised 230 vessel segments. From infrarenal aorta to distal femoral arteries, DECT showed higher CNR compared to DSA and MDCT ( P < .05); distal to the popliteal arteries, DSA achieved higher CNR ( P < .05). Analyses of contrast homogeneity showed minimal CV above the knee for MDCT (≤9%) and for DSA below the knee (≤7%). Stenotic vasculature comprised 33 segments. Significant correlations of stenosis severity were found comparing DECT and MDCT with DSA as reference standard showing a 0.04-fold mean underestimation of stenoses on MDCT and no detectable mean variation on DECT compared with DSA.
Conclusion
DECT angiography improved contrast in vascular abdominopelvic and thigh distributions beyond MDCT angiography and DSA while preserving the ability to precisely assess severity of stenoses, using DSA as an accepted reference standard.
Traditionally, peripheral arterial disease has been evaluated with digital subtraction angiography (DSA). Multidetector computed tomography (MDCT) angiography, however, represents a noninvasive alternative to conventional DSA for the evaluation of the peripheral arterial vasculature as MDCT angiography requires a less invasive technique for contrast agent administration and, furthermore, allows evaluation of the vascular lumen as well as vessel wall . DSA employs a precontrast mask to mathematically eliminate extraluminal anatomy. MDCT angiography uses threshold-based postprocessing techniques to extract vascular anatomy, which are, however, inherently nonspecific to types of contrast agents and further compromised by beam hardening phenomena originating from mural calcifications and vascular stents .
Selective iodine extraction with beam hardening correction through pixel-by-pixel data postprocessing has become possible with dual-energy computed tomography (DECT) technology. In DECT imaging, 2 x-ray beams of distinct and known energy spectra are tuned to the characteristic absorption profiles of injected contrast materials. This technology may enable selective contrast agent extraction and, furthermore, correct for beam hardening phenomena without substantially increasing the radiation dose to the patient . Prior studies have shown qualitatively DECT angiography to improve sensitivity and specificity for detecting peripheral arterial disease in the lower extremities compared to MDCT angiography and DSA .
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Materials and methods
Patient Recruitment
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DECT MDCT Acquisition and Spectral Iodine Extraction
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DSA
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Assessment Parameters
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Statistical Analysis
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Results
Vascular Contrast in Patent Abdominopelvic and Lower Extremity Vasculature
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Table 1
Vascular Contrast Analysis of the Patent Abdominopelvic and Lower Extremity Vasculature: Statistical CNR Assessment (Source Data Given in Fig 1 )
Vessel Segments CNR of Imaging Series Abdominopelvic/Lower Extremity
Vasculature
n = 230 Highest CNR Lowest CNR Abdominopelvic distribution
n = 78 Infrarenal aorta n = 15 DECT P < .0001 » DSA P = .259 > MDCT P < .0001 Common iliac artery n = 29 DECT P < .0001 » MDCT P = 1.0 > DSA P < .0001 External iliac artery n = 34 DECT P < .0001 » DSA P = 1.0 > MDCT P < .0001 Thigh distribution
n = 106 Common femoral artery n = 34 DECT P < .0001 » MDCT P = .467 > DSA P < .0001 Profunda femoral artery n = 25 DECT P < .0001 » DSA P < .012 » MDCT P < .0001 Superficial femoral artery n = 27 DECT P < .0001 » DSA P = .031 » MDCT P < .0001 Popliteal artery n = 20 DECT P = .349 > DSA P = .151 > MDCT P < .0001 Calf distribution
n = 46 Anterior tibial artery n = 11 DSA P < .0001 » MDCT P < .0001 » DECT P < .0001 Tibioperoneal trunk n = 14 DSA P = .006 » DECT P = 1.0 > MDCT P = .002 Peroneal artery n = 12 DSA P = 1.0 > MDCT P < .0001 » DECT P < .0001 Posterior tibial artery n = 9 DSA P < .0001 » MDCT P = .043 > DECT P < .0001
CNR, contrast-to-noise ratios; DECT, dual-energy MDCT; DSA, digital subtraction angiography; MDCT, multidetector computed tomography; », statistical significance; subscript P values are based on 1-way analysis of variance comparisons.
Comparison of CNR characteristics of the 11 vascular anatomic levels achieved by DSA, DECT, and MDCT series with corresponding P values. Comparisons are made with the image series to the right/first image series.
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Table 2
Vascular Contrast Analysis of the Patent Abdominopelvic and Lower Extremity Vasculature: Statistical CV Assessment (Source Data Given in Fig 1 )
Vessel Segments CV of Imaging Series Abdominopelvic/Lower Extremity
Vasculature
n = 230 Lowest CV Highest CV Abdominopelvic distribution
n = 78 Infrarenal aorta n = 15 MDCT P = .596 > DECT P = .351 > DSA P = .017 Common iliac artery n = 29 MDCT P = 1.0 > DSA P = .039 » DECT P = .012 External iliac artery n = 34 MDCT P = 1.0 > DSA P = .093 > DECT P < .008 Thigh distribution
n = 106 Common femoral artery n = 34 MDCT P = 1.0 > DSA P = .828 > DECT P = .376 Profunda femoral artery n = 25 MDCT P = 1.0 > DSA P = .014 » DECT P = .002 Superficial femoral artery n = 27 MDCT P = 1.0 > DSA P < .0001 » DECT P < .0001 Popliteal artery n = 20 DSA P = 1.0 > MDCT P < .0001 » DECT P < .0001 Calf distribution
n = 46 Anterior tibial artery n = 11 DSA P = .329 > MDCT P = .001 » DECT P < .0001 Tibioperoneal trunk n = 14 DSA P = .138 > MDCT P = .068 > DECT P < .0001 Peroneal artery n = 12 DSA P = .511 > MDCT P = .021 » DECT P < .0001 Posterior tibial artery n = 9 DSA P = .041 » MDCT P = .007 » DECT P < .0001
CV, coefficient of variation; DECT, dual-energy MDCT; DSA, digital subtraction angiography; MDCT, multidetector computed tomography; », statistical significance; subscript P values are based on 1-way analysis of variance comparisons.
Comparison of coefficients of variation of the 11 vascular anatomic levels achieved by DSA, DECT, and MDCT series with corresponding P values.
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Analysis of Stenotic Abdominopelvic and Lower Extremity Vasculature
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Table 3
Vascular Analysis of the Stenotic Abdominopelvic and Lower Extremity Vasculature: Statistical Stenoses Assessment
Vessel Segments Analyses of Image Series Abdominopelvic/Lower Extremity
Vasculature
n = 33 Comparison: 2-tailed paired t -test
Correlation: bivariate Pearson correlation DSA vs. MDCT DSA vs. DECT Abdominopelvic distribution
n = 12P__t -test = .1715P__t -test = .9323r Pearson = 0.955r Pearson = 0.839 Sig. Pearson < 0.0001 Sig. Pearson = 0.0012 Infrarenal aorta n = 3 Common iliac artery n = 5 External iliac artery n = 4 Thigh distribution
n = 21P__t -test = .3248P__t -test = .9728r Pearson = 0.498r Pearson = 0.484 Sig. Pearson = 0.0221 Sig. Pearson = 0.0264 Common femoral artery n = 3 Superficial femoral artery n = 13 Popliteal artery n = 5
DECT, dual-energy MDCT; DSA, digital subtraction angiography; MDCT, multidetector computed tomography.
Paired t -test comparison and bivariate Pearson correlation of stenoses severities of 33 vascular segments based on DSA, DECT, and MDCT series with corresponding P values (paired t -tests comparison) as well as correlation coefficient r with corresponding significance level (bivariate Pearson correlation). No statistically significant difference in assessment of degree of stenosis was detected between DSA, DECT, and MDCT series; significant correlations of detected stenosis severities were found.
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Discussion
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