Iterative recon marshals 'profound effect' on CT scanning

Iterative reconstruction algorithms will have a “profound effect” on CT as the enabling technology for advances in image quality and patient safety, said Stanford radiology professor Geoffrey Rubin at the ISCT symposium on multidetector row CT.

For more than a year, vendors have been framing their own brands of iterative reconstruction algorithms as the means for improving image quality and, thereby, reducing patient radiation dose. These algorithms are designed to do more with fewer photons, allowing radiologists to dial back the kilo voltage (kV) that drives x-ray tubes and the mAs (milliamperes) that define tube current. But IR software can do much more than just cut dose, Rubin said.

“Just about every aspect of image quality and patient safety relating to the CT scanning will be impacted in a positive way by iterative reconstruction,” he said.

Rubin kicked off the ISCT symposium May 18 with an early morning lecture that traced the development of multidetector row CT to 1998 and the introduction of the first quad-row scanner. Advances over the last dozen years have boosted temporal and spatial resolution as the number of rows has increased exponentially, leading to wide area detectors, multiple x-ray sources, high-pitch scanning, and spectral imaging. But the most recent of these, iterative reconstruction, may be the most significant.

“One obvious benefit (of IR) is the ability to reduce radiation exposure because we can use fewer photons to image the patient and still get a high level of quality,” Rubin told Diagnostic Imaging in an interview after his lecture. “But another is its effect on quality, in that it enables us to effectively use lower beam energies, which not only compounds the radiation dose benefit but enables us to much better separate out the differences in attenuation between calcium and iodine. This allows us to reduce the amount of iodine (contrast medium) yet still achieve the same enhancement or even get superior enhancement.”

Current and future algorithms that incorporate iterative reconstruction hold out the further prospect of scanning faster and with higher temporal resolution while maintaining image quality, he said.