Researchers have developed software for radiologists to capture more accurate images of moving organs, reducing the number of misdiagnoses and patient recalls.
The project, from Oxford University's technology transfer company Isis Innovation, concentrated on creating software for abdominal magnetic resonance imaging (MRI) systems to acquire stable images of the liver, which moves when people breathe.
'Typically in magnetic resonance imaging, to acquire an image of the whole liver, you would need somebody to hold their breath for 60 seconds. Chances are that the patient is not particularly healthy, so it is expecting quite a lot,' said Dr Jamie Ferguson, Isis project manager.
In existing methods of magnetic resonance imaging, the patient holds his or her breath for 20 seconds at a time while the machine takes an image of the liver in slices. After 60 seconds the slices are then put back together to form a whole image. Because the liver may move in between breath holds, some of the slices may overlap, or they might be put together incorrectly.
The researchers claim the new technology would eliminate this problem by aligning the slices of the liver image to a reference volume, an outline image of the liver taken before the more detailed slices, automatically checking for overlaps or missing slices.
'The reference image is acquired with a T1 weighted fast spoiled gradient echo (FSPGR) image. This can be acquired in a single breath hold of 15 to 20 seconds,' said Olivier Noterdaeme, a PhD student who worked on the project.
'T2 images always take longer to acquire. Dependent on liver size and image resolution, the acquisition of the T2 images of the whole liver typically takes about 80 seconds. But because this is too long, you break it down into several, shorter breath holds, like 20 seconds each, so you take four images. But you need both the T1 and T2 images to make the diagnoses, as they provide complementary information.' T1 and T2 are terms that refer to the physical properties of the tissue.
Existing MRI techniques result in a jagged image with the slices clearly visible, but the image produced using the new technology shows the liver as having a smooth outline and no obvious joins.
To test the quality of the images, the researchers showed a set of 2D slices from the existing scanner to experienced radiologists and asked them to count the number of lesions. They found that on two occasions, the radiologists mistook large, continuous lesions for multiple lesions because the slices were not in order. When this was corrected, the lesions were all correctly identified.
'The technology can identify and correct any flawed regions of that image. If you have a tumour in the liver which is not continuous, you could assume it was two tumours. but it is also likely that you have put the images back together incorrectly and the slices are in the wrong order,' said Ferguson.
By installing the software into existing or new MRI systems, the researchers believe that a large number of MRI datasets would see an improvement. 'We estimate that around 25 per cent of two million abdominal MRI scans done every year worldwide would benefit. You will be more assured that you have imaged the whole liver, which means you would be less likely to have to recall a patient, which can cause trauma and creates issues with waiting lists,' said Ferguson.
Once the technology has been successfully tested for liver imaging, the scientists hope to extend the application of the software to view different organs and for use in different imaging systems, such as CT (computed tomography) and single-photon emission computed tomography (SPECT).
'The advantage of the technique is that it is applicable to organs subject to large uncontrolled amounts of motion. An extension of the technology would be the imaging of the head or body parts of patients who suffer from Parkinson's disease and cannot control their motions,' said Noterdaeme.