Evaluation of an iterative model-based CT reconstruction algorithm by intra-patient comparison of standard and ultra-low-dose examinations

Abstract

Background The explosive growth of computer tomography (CT) has led to a growing public health concern about patient and population radiation dose. A recently introduced technique for dose reduction, which can be combined with tube-current modulation, over-beam reduction, and organ-specific dose reduction, is iterative reconstruction (IR). Purpose To evaluate the quality, at different radiation dose levels, of three reconstruction algorithms for diagnostics of patients with proven liver metastases under tumor follow-up. Material and Methods A total of 40 thorax-abdomen-pelvis CT examinations acquired from 20 patients in a tumor follow-up were included. All patients were imaged using the standard-dose and a specific low-dose CT protocol. Reconstructed slices were generated by using three different reconstruction algorithms: a classical filtered back projection (FBP); a first-generation iterative noise-reduction algorithm (iDose4); and a next generation model-based IR algorithm (IMR). Results The overall detection of liver lesions tended to be higher with the IMR algorithm than with FBP or iDose4. The IMR dataset at standard dose yielded the highest overall detectability, while the low-dose FBP dataset showed the lowest detectability. For the low-dose protocols, a significantly improved detectability of the liver lesion can be reported compared to FBP or iDose ( P = 0.01). The radiation dose decreased by an approximate factor of 5 between the standard-dose and the low-dose protocol. Conclusion The latest generation of IR algorithms significantly improved the diagnostic image quality and provided virtually noise-free images for ultra-low-dose CT imaging.

CNN as model observer in a liver lesion detection task for x‐ray computed tomography: A phantom study

“…) for the training step because we wanted to see if such observers can predict the performance in images with decreased image quality. Compared to the analytical FBP, iDose is an iterative reconstruction algorithm which reduces image noise …”

“…The models were trained with data reconstructed with iDose and evaluated on data reconstructed with FBP to ensure a realistic setup where a MO is used to evaluate a new modality or algorithm. FBP is expected to deliver images with more image noise and a decreased image quality compared to iterative iDose . This way, we wanted to ensure that the models can also detect lower image qualities, thus, algorithms with worse performance can be identified.…”

Ultra‐low dose CT colonography with automatic tube current modulation and sinogram‐affirmed iterative reconstruction: Effects on radiation exposure and image quality

“…5,9 Many noise reduction methods based on image-based iterative reconstruction algorithms have been developed for CT imaging and recent studies demonstrated the feasibility of low-dose (LD) protocols beneficiating of comparable image quality and diagnostic performance. [10][11][12][13] Sinogram-Affirmed Iterative Reconstruction (SAFIRE, Siemens Healthcare, Erlangen, Germany) is a hybrid iterative reconstruction technique incorporating a raw data-based iterative reconstruction algorithm and an image space iteration algorithm. 14,15 Low-dose and ultra-low dose (ULD)-CTC have been demonstrated to be feasible to reduce radiation dose maintaining a comparable image quality when using iterative reconstruction technique.…”

Can optimized model-based iterative reconstruction improve the contrast of liver lesions in CT?

“…Pickhardt et al were able to maintain a sensitivity of 79.3% for abdominal lesions with an MBIR algorithm while reducing the dose by an average of 74% (18). Noël et al showed a significantly better detection with MBIR than with HIR and FBP in 77.9% reduced dose CT images (32). Choi et al were able to maintain a sensitivity of 97.9% for liver lesions while reducing the dose by one-third with an MBIR algorithm (33).…”