Topics covered in this article include:
- Measurement Summary
- Available Tests
- Detailed Discussion of Measurements
- Example File
The MV-QA is a common phantom designed to be used weekly and/or monthly to provide an ongoing check of imaging performance, particularly those aspects which are most liable to deterioration. After an initial grey-scale check, image quality is measured simply by counting the number of details detected and the number of bar patterns resolved in the image. Two images are required for comparison for all tests to complete. An ongoing record of these numbers will reveal any trend towards deterioration in imaging performance.
Task Group 142 (TG-142) of the American Association of Physicists in Medicine (AAPM) recommends that Planar MV Imaging should be checked during monthly Quality Assurance (QA) in Table VI: Imaging.
The analysis provides the following results:
- Normalized MTF Plot
- MTF Critical Frequencies
- Contrast to Noise Ratio
- Position Offset from Center
- Center Pixel
The measurements are completely automated, requiring the user only to drag and drop the image set into the web-based software interface. A detailed report is created.
The test requires at least one image and it must be a DICOM file. The files must contain "sncmv" somewhere in the file name. Alternatively, limited capabilities to manually identify planar images using DICOM tag values have been added to the image processing system. This is an extension of the existing naming convention system. For more details see Manual Identification of RT Planar Images and Individual Catphan Slices through DICOM tags.
When imaging QA tests are added to templates an upload control will appear in the scheduled QA's data entry screen allowing the user to upload images for automated analysis.
To add files to the upload queue simply drag them from a Windows Explorer folder to the drag and drop folder and release them. Alternatively, by clicking on the Add Files button to the lower right of the control a windows file selection dialog will open and files can be selected for upload. Under either method, multiple files may be selected for upload at once.
If the automatically upload checkbox is checked (the default) then file uploading will start immediately as files are added.
If the automatically upload button is turned to off the file upload process must be started manually clicking the Start upload button on the lower right of the control. To clear the upload queue click the Clear button.
Once file series have been uploaded they will be displayed below the upload control. To remove a series from the queue click the Cancel button beside the series. To start processing click the Start Processing button. A description for the image series can be added at this point. Click the Edit button next to the series. Type a description for the series into the text box that appears below Description and either click Save or press the enter key. The description can also be edited after the images have been processed. Descriptions will appear in the report with the analysis of the series.
While files are being processed users may perform other tasks such as data entry.
The following tables show the tests to select in the template builder corresponding to the supported analyses.
|Planar MV Imaging||Monthly Imaging QA [TG142 Table VI]||Planar MV Imaging (SNC MV)|
Image Acquisition Suggestions
Below are the recommended steps to acquire the images:
- Align the phantom in the stand so that the two sagittal alignment markers are visible.
- Place the MV-QA phantom at isocenter.
- Align the phantom so that the light field cross-hairs or room lasers match the cross-hairs on the face of the phantom and the sagittal alignment markers on the top of the phantom.
- Raise the EPID as close as possible to the phantom to minimize image magnification.
- Acquire an MV image of the phantom.
Detailed Discussion of Measurements
Contrast, Noise, and Contrast to Noise Ratio (CNR) are calculated as shown below:
Area refers to the areas marked in the picture below:
Below is an example of the report generated from the asymmetric field test:
Below is an example file for use in testing: