Rationale and Objectives
The aim of this study was to evaluate whether the spectral characterization of the iodine content of lung microcirculation could help identify ground-glass opacity (GGO) of vascular origin.
Materials and Methods
Thirty-five consecutive patients with GGO of bronchioloalveolar (group 1; n = 24) and vascular (group 2; n = 11) origin underwent dual-energy multi-detector computed tomographic angiography of the chest using a standard injection protocol. For each patient, two radiologists evaluated by consensus the presence, location, and extent of GGO on diagnostic computed tomographic scans (ie, contiguous 1-mm-thick averaged images from both tubes) and characteristics of the corresponding areas on perfusion scans.
Results
A total of 443 segments with GGO were depicted on the diagnostic scans (group 1, n = 231; group 2, n = 212), always intermingled with areas of normal lung attenuation, with a mean of 12.7 segments with GGO per patient. Areas of GGO were located at the level of the upper lobes ( n = 128), middle lobe and/or lingula ( n = 81), and lower ( n = 234) lobes, involving <25% ( n = 165), 25% to 50% ( n = 103), 50% to 75% ( n = 155), and >75% ( n = 20) of the segmental surface. The overall quality of perfusion scans was rated as interpretable in all patients. Perfusion scans depicted areas of hyperattenuation within segments of GGO with a significantly higher frequency in group 2 (211 of 212 [99.5%]) than in group 1 (27 of 231 [12%]) ( P < .0001). Hyperattenuated areas of vascular origin were observed to match the areas of GGO in surface (203 of 211 [96%]) and contours (208 of 211 [98.6%]).
Conclusion
Dual-energy computed tomography can help recognize GGO of vascular origin.
On computed tomographic (CT) imaging, ground-glass opacity (GGO) is defined as hazy increased opacity of the lung, with preservation of bronchial and vascular margins , which can be observed as a diffuse increase in lung attenuation or as a disseminated abnormality, resulting in areas of variable lung attenuation. This pattern of lung attenuation presents a challenge for radiologists, who must first recognize it and then relate it to the most likely underlying disease. Relying on the visual assessment of lung parenchymal attenuation, this CT pattern is sometimes difficult to depict on high-resolution CT images, especially when of mild severity, which has led to the development of automatic detection and quantification tools .
The second difficulty for radiologists is the nonspecificity of GGO, which has been described in a large variety of disorders, a logical finding when considering that lung attenuation results from the relative proportions of blood, gas, extravascular water, and pulmonary tissue . From a pathophysiologic standpoint, GGO may thus be caused by partial filling or collapse of the airspaces, interstitial thickening, or both, but it may also result from regional or diffuse increase in capillary blood volume. In the latter situation, it is most commonly due to a redistribution of blood flow as a consequence of destructive and/or obstructive changes at the level of the pulmonary circulation, which can be seen in a variety of bronchopulmonary and vascular disorders, such as emphysema, airway diseases, pulmonary arterial hypertension, and pulmonary or venous obstruction . Often described as mosaic perfusion, GGO of hemodynamic origin can be recognized on high-resolution CT images by the presence of increased vascular diameters through the areas of increased lung attenuation, sometimes seen with well-defined borders conforming to the boundaries of secondary pulmonary lobules .
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Materials and methods
Population
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Scanning Protocol
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Reconstructed Scans
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CT Parameters Analyzed
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Conditions of CT Interpretation
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Statistical Analysis
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Results
Analysis of Diagnostic Scans
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Table 1
Characteristics of GGO on Diagnostic Scans in Groups 1 and 2
Group 1: GGO Due to Airspace Disease Group 2: GGO Due to Redistribution of Blood Flow ( n = 231) ( n = 212) Segments with isolated GGO ( n = 389) 226 (98%) 163 (77%) Segments with GGO and dilated vascular sections ( n = 54) 5 (2%) 49 (23%)
GGO, ground-glass opacity.
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Side-by-Side Analysis of Diagnostic and Perfusion Scans
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Evaluation of Perfusion Scan Information
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Table 2
Perfusion Scan Findings in the 54 Segments with GGO and Dilated Vascular Sections on Diagnostic Scans in Groups 1 and 2
Group 1: GGO Due to Airspace Disease Group 2: GGO Due to Redistribution of Blood Flow_P_ ∗ Segments with GGO and increased vascular sections on diagnostic scans ( n = 54) 5 49 <.0001 Degree of attenuation within the 54 segments with GGO and increased vascular sections on diagnostic scans Mild (score 1) 0 10 Moderate (score 2) 0 22 High (score 3) 5 17 Hyperattenuation on the corresponding segments on perfusion scans 0 (0%) 49 (100%) Not applicable
GGO, ground-glass opacity.
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Table 3
Perfusion Scan Findings in the 389 Segments with Isolated GGO on Diagnostic Scans in Groups 1 and 2
Group 1: GGO Due to Airspace Disease Group 2: GGO Due to Redistribution of Blood Flow_P_ ∗ Segments with isolated GGO on diagnostic scans ( n = 389) 226 163 Degree of attenuation within the 54 segments with GGO and increased vascular sections on diagnostic scans Mild (score 1) 36 90 Moderate (score 2) 43 73 High (score 3) 147 0 Hyperattenuation in the corresponding segments on perfusion scans 27 (11.95%) 162 (99.4%) <.0001
GGO, ground-glass opacity.
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Discussion
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subgroup of GG
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Conclusion
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