Advances in magnetic resonance imaging to quantify the blood flow in the heart and major vessels stemming from the heart has recently allowed for advanced clinical applications for patients suffering from cardiac valve problems and aortic abnormalities. 7D cardiac flow quantification is relatively new, but has already shown potential in several clinical applications, including bicuspid valve and aortic coarctation characterization. In addition radiologists diagnosing valvular regurgitation may benefit from insight provided by the 7D cardiac flow quantification protocol.
7D cardiac flow quantification using magnetic resonance imaging will provide direction flow quantification in the anterior / posterior, head / foot, and left / right directions, in time, through the imaging volume. Providing MRI techniques that may lead to clinical applications to characterize the cardiac valves, the flow differentials during cardiac function, and the flow and pressure differentials of the aortic arch, as well as automation of the delayed reconstruction process for raw data, are the main focus of this study.
The study was approached in four stages. First, using the Philips ExamCard environment, a scan protocol was developed. The scan protocol provided the anatomical views for the 7D flow quantification in the heart. Execution of the ExamCard provides two anatomical areas of focus, the aortic arch and the valve plane of the heart. Raw data was saved to the scanner’s database, for later reconstruction.
A second stage of the project was completed to verify the ExamCard and manual reconstruction had been properly developed. To do so, four volunteer studies were completed. Each volunteer was scanned on the same Philips 1.5T Achieva scanner, using the 7D flow ExamCard developed in stage one, and raw data reconstructed using the manual delayed reconstruction procedure. Flow quantification in a 3D volume in 3 directions over time was verified. Results were verified using existing studies as a gold standard.
Because manual delayed reconstruction is time consuming, and may lead to errors, automation of the delayed reconstruction is desired. A third stage of the project was aimed at automation of the delayed reconstruction process.
The third stage of the project involved writing a batch file to automate the reconstruction of the raw data saved from the previously described scan protocol. The batch file is an executable script file that will automate the manual work of the Philips delayed reconstruction procedures. The batch file, when executed, will select, change reconstruction parameters for each of the 2 anatomical areas, in three different directions, for a total of 6 scan reconstructions, run the reconstruction, and name the scans appropriately. Using raw data of the four volunteer studies in stage 2, the batch file was tested.
The focus then shifted to a fourth stage of the project. The focus was verifying the results of the automation versus the manual delayed reconstruction process.
Using standard Philips Achieva analysis software, reports for all manual, automated, and “subtraction” data sets were generated. These reports were compared. In all cases, both the manual and automated data sets produced analysis exactly the same for the given parameters. The “subtraction” data set further proved the manual and automated data sets were the same by analysis where all measured parameters were zero, proving the hypothesis and demonstrating the automated batch file did indeed reconstruct the raw data equivalent to reconstruction produced using the standard manual delayed reconstruction package from Philips.
Finally, the data sets from the automated reconstruction were used to plot velocity profiles across regions of interest and compare results between operators as well as patients.
The project was completed at the Philips Healthcare facility located at 595 Miner Rd, Highland Heights, OH, in conjunction with the Cleveland Clinic Foundation of Cleveland, Ohio.