Photon-counting computed tomography uses energy-resolving detectors, thereby enabling scanning at multiple energies.

Technique

Physical principles

Clinical CT systems rely on energy-integrating detectors, which measure the total x-ray energy reaching the detector during the measurement period. The photon-counting detectors in a photon-counting CT system count the exact number of incoming x-ray photons and also measure their energy individually. As a consequence, photon-counting detectors always obtain spectral information and can effectively filter out electronic noise, unlike energy-integrating detectors, resulting in a significantly improved signal-to-noise ratio ^1,2. 

History and etymology

The first commercial photon-counting CT scanner was introduced by Siemens and has been approved by the US Food & Drug Administration (FDA) in 2021 ³.

Initial technical challenges were primarily posed by cross-talk between the detector elements and the extremely fast detector readout required to separately count each incident x-ray photon ^1,2. Early clinical results demonstrate a substantial improvement in spatial resolution and reduction of noise compared to the existing state-of-the-art CT systems ⁴.

Practical points

Photon-counting CT readily differentiates between tissue types and contrast agents using spectral CT with improved virtual non-contrast images and measurements, giving the exact concentration of materials within the voxel (e.g. calcium, iodine), resulting in improved accuracy of perfusion and ventilation measurements, kidney stone characterization, etc ². Portable scanners have been developed for head CT and extremity CT ⁸.

Expanded and improved applications of CT potentially include ⁸:

• improved temporal, spatial and contrast resolution

• fewer artefacts (blooming and beam-hardening)

• lower radiation dose

• higher signal to noise ratio

• new contrast media, alone or in combination e.g. gadolinium, gold nanoparticles

• lesion conspicuity e.g. liver lesions

• detection of smaller calcific foci

• chemotherapy quantification in the body to assess effects of treatment

• grey-white matter differentiation

• assessment of coronary artery stent patency

• classification of lung nodules and masses

• characterization of renal cysts

• plaque assessment

• detail of small vessels

• definition of IPMN and main pancreatic duct

• temporal bone resolution

• liver fat fraction analysis

• identification of CSF-venous fistulae in spontaneous intracranial hypotension

• opportunistic screening of bone mineral density and biomarkers