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    Keywords: Germany ; LUNG ; PERFUSION ; imaging ; VENTILATION ; DIFFERENTIATION ; RESOLUTION ; PATIENT ; IMPACT ; image analysis ; MR ; MRI ; SEQUENCE ; SIGNAL ; MAGNETIC-RESONANCE ; magnetic resonance imaging ; ACQUISITION ; REQUIRES ; SCINTIGRAPHY ; ABNORMALITIES ; acquisitions (GRAPPA) ; ANGIOGRAPHY ; CONTRAST-ENHANCED MRI ; generalized autocalibrating partially parallel ; magnetic resonance imaging (MRI) ; parallel imaging techniques ; PULMONARY PERFUSION
    Abstract: Rationale: Contrast-enhanced magnetic resonance imaging (MRI) of lung perfusion requires a high spatial and temporal resolution. Partially parallel MRI offers an improved spatial and temporal resolution. Objective: To assess the feasibility of partially parallel MRI for the assessment of lung perfusion. Methods: Two healthy volunteers and 14 patients were examined with a contrast-enhanced 3D gradient-echo pulse sequence with partially parallel image acquisitions (TE/TR/alpha: 0.8/1.9 milliseconds/40degrees; voxel size 3.6 X 2.0 X 5.0 mm(3), TA: 1.5 seconds). The image analysis included an analysis of the signal-to-noise ratio in the lungs in areas with normal and impaired perfusion. 3D MR perfusion image data were analyzed for perfusion defects and compared with radionuclide perfusion scans, which were available for 10 of 14 patients. Results: The analysis of the 3D perfusion-weighted data allowed a clear differentiation of perfusion abnormalities: MRI showed normal lung perfusion in 9 of 16 cases, whereas perfusion abnormalities were observed in 7 cases. When compared with the radionuclide perfusion scans, a good intermodality agreement was shown (kappa = 0.74). When compared with normally perfused lung a significantly lower signal to noise ratio was observed in hypoperfused lung (7 versus 17; P = 0.02). Conclusion: Partially parallel MRI might be used for the assessment of lung perfusion. Future studies are required to further evaluate the diagnostic impact of this technique
    Type of Publication: Journal article published
    PubMed ID: 12874514
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