Discussing the value of ultrahigh-resolution CT scanning

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Discussing the value of ultrahigh-resolution CT scanning

par Gus Iversen, Editor in Chief | September 10, 2019
CT X-Ray
From the September 2019 issue of HealthCare Business News magazine


HCB News: What does ultrahigh-res mean in terms of CT scan image quality? Does it open up new capabilities?
JB: We are all aware of the various modalities available in the radiology department for imaging patients and, of course, each of these modalities has its strengths and weaknesses. Traditional resolution CT imaging excels at contrast resolution (the ability to see large lesions with subtle contrast differences) but is not particularly exciting when it comes to spatial resolution (the ability to see small objects) – which for most clinical CT scanners the smallest resolvable element is on the order of 0.50 mm. But with this new CT scanner, we have the ability to resolve 0.15 mm voxels; and the obvious question is, “What human anatomy has spatial features on the scale from 0.15 to 0.5 mm?” The answer to this is the answer to your question about “new capabilities”. We believe that the increase in spatial resolution achievable by this new CT scanner technology will allow meaningful improvement in diagnoses involving lung parenchyma, the anatomy of trabecular bone (in trauma and disease), liver texture, and microvasculature — the latter of which includes diagnoses related to cancer, vascular disease, and a whole host of other pathologies. Thus, the prospective capabilities of this scanner are exciting to me, and through clinical trials we are trying to methodically evaluate which specific areas of CT imaging this new device will advance.

HCB News: Can you provide any examples of how those exceptional images have impacted diagnostics for your patients?

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JB: Your readers will recognize that as the voxel dimensions of the CT image get smaller, the spatial resolution increases, but so does the quantum noise. At the same radiation dose levels, fewer X-ray photons traverse a smaller voxel relative to a larger voxel, so consequently, there will be larger quantum noise levels when the smaller voxels are reconstructed. When the Canon scientists presented this technology to me and a group of other medical imaging scientists, of course this was the first question that came to mind. Initially the solution to decrease quantum noise with the high-resolution images was dealt with using iterative reconstruction techniques, which have become the industry standard method for noise suppression in CT over the past decade. I was frankly impressed to find that this manufacturer has also developed CT reconstruction methods designed to reduce noise based upon artificial intelligence techniques — their deep learning reconstruction algorithm. I’m very excited to see how the DLR algorithm reduces noise in the high-resolution images, however this software was only recently FDA approved and is about to be installed on our scanner in the next week or two. For many applications, we were waiting for the DLR algorithm in order to fully assess the system clinically, and we now have our sleeves rolled up to do so. So please ask me this question in a year or so, and I will have a better answer after we have done the research.

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