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Regional lung perfusion: assessment with partially parallel three-dimensional MR imaging
Authors:Fink Christian  Puderbach Michael  Bock Michael  Lodemann Klaus-Peter  Zuna Ivan  Schmähl Astrid  Delorme Stefan  Kauczor Hans-Ulrich
Institution:Department of Radiology, Deutsches Krebsforschungszentrum, Innovative Krebsdiagnostik und Therapie, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. c.fink@dkfz.de
Abstract:PURPOSE: To evaluate partially parallel three-dimensional (3D) magnetic resonance (MR) imaging for assessment of regional lung perfusion in healthy volunteers and patients suspected of having lung cancer or metastasis. MATERIALS AND METHODS: Seven healthy volunteers and 20 patients suspected of having lung cancer or metastasis were examined with 3D gradient-echo MR imaging with partially parallel image acquisitions (fast low-angle shot 3D imaging; repetition time msec/echo time msec, 1.9/0.8; flip angle, 40 degrees; acceleration factor, two; number of reference k-space lines for calibration, 24; field of view, 500 x 440 mm; matrix, 256 x 123; slab thickness, 160 mm; number of partitions, 32; voxel size, 3.6 x 2.0 x 5.0 mm(3); acquisition time, 1.5 seconds) after administration of 0.1 mmol/kg of gadobenate dimeglumine. In volunteers, 3D MR perfusion data sets were assessed for topographic and temporal distribution of regional lung perfusion. Sensitivity, specificity, accuracy, and positive and negative predictive values for perfusion MR imaging for detecting perfusion abnormalities in patients were calculated, with conventional radionuclide perfusion scintigraphy as the standard of reference. Interobserver and intermodality agreement was determined by using kappa statistics. RESULTS: Topographic analysis of lung perfusion in volunteers revealed a significantly higher signal-to-noise ratio (SNR) of up to 327% in gravity-dependent lung areas. Temporal analysis similarly revealed much shorter lag time to peak enhancement in gravity-dependent lung areas. In patients, perfusion MR imaging achieved high sensitivity (88%-94%), specificity (100%), and accuracy (90%-95%) for detection of perfusion abnormalities. Interobserver agreement (kappa = 0.86) was very good and intermodality agreement (kappa = 0.69-0.83) was good to very good for detection of perfusion defects. A significant difference (P <.0001) in SNR was observed between normally perfused lung (14 +/- 7 SD]) and perfusion defects (7 +/- 4) in patients. CONCLUSION: Partially parallel MR imaging with high spatial and temporal resolution allows assessment of regional lung perfusion and has high diagnostic accuracy for detecting perfusion abnormalities.
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