Journey Of CT, moving on

Since the introduction of computed tomography (CT) in 1972, there has been a tremendous advancement in the technology which led to improvement in image quality with reduced scan time and decreased radiation exposure. Faster scan speed and high resolution are of great concern especially in the field of cardiac imaging and for pediatric imaging. Introduction of multislice CT scanners with an increased number of detector elements, dual energy CT scanners, and iterative reconstruction methods are the biggest achievements that made CT as the most reliable, feasible and affordable imaging technique. Though various multislice CT scanners were provided by Philips, GE and Siemens including 64 slice, 128 slice, 256 slice, 320 slice, and 640 slice scanners, many radiologists consider 64 slice CT to be sufficient for the image quality required, even for coronary angiography.

Imaging the beating heart without motion artifacts was one of the greatest challenges faced by radiologists, which was made feasible by the introduction of 64 and higher slice CT scanners. With the use of more sensitive detectors, higher gantry speed and use of iterative and model-based image reconstruction software, the whole of the cardiac imaging can be accomplished in one heartbeat precisely and the radiation dose has been reduced from 15-20 mSv to 3 mSv or less. The Dual-source CT scanners improve the temporal resolution exponentially and obviate the need for lowering the heart rate, making CT coronary angiography a truly walk-in OPD procedure. Newer cardiac imaging techniques like coronary plaque assessment, CT perfusion imaging and fractional flow reserve (FFR CT) allow a functional assessment in addition to anatomical assessment, thus reducing the need for nuclear perfusion studies and invasive coronary angiography.

In addition, CT calcium scoring system and epicardial fat estimation can be used as risk assessment tools for screening coronary disease. Dual-energy CT scanner is other advancement in the history of CT, which images the same organ at two different kV energies, which can be accomplished by using two different energy sources or a single source that allows faster kV switching between two different energy levels. The tissues will produce different attenuation properties at different energy levels in single scan time, thus reducing the need for multiple scans. In addition, its software can highlight or eliminate specific compounds like iodine, calcium and other metals depending on their atomic number, thus producing both contrast and non-contrast images from a single contrast scan. This has an application in pulmonary thrombus assessment, identification of the type of renal stones and its management, reduction of the metal artifact, assessment of gout etc.

CT perfusion imaging has a clinical role in neurovascular, oncologic, and cardiovascular applications. The time – attenuation curve over the tissue/organ of interest is used, with various models of single- and multiple-compartment flow, in order to estimate parameters such as absolute blood flow and volume and vascular permeability. Siemens, GE, and Philips have already received FDA 510(k) clearance for post-processing software packages for CT brain perfusion and now they are preparing post-processing software for cardiac CT perfusion.

CT scanner vendors have developed various image reconstruction techniques in order to reduce the image noise and radiation dose. One such technique is iterative reconstruction, known by the trade names iDose (Philips), Iterative Reconstruction in Image Space (IRIS; Siemens), Adaptive Iterative Dose Reduction (AIDR; Toshiba), and Adaptive Statistical Iterative Reconstruction (ASiR; GE Healthcare). The PET-CT hybrid has revolutionized medicine. The molecular imaging with tissue-specific antigens has taken a notch above computer aided detection, to computer aided prediction of response and computer aided biologic profiling.

Future CT scanners will aim at further improving the scan speed and advanced image reconstruction software along with improved detector resolution which will further lower the radiation dose. Incorporating Artificial Intelligence, radionics, and deep learning into the scanners will bring in more promise.