Feasibility of low-dose CT with model-based iterative image reconstruction in follow-up of patients with testicular cancer.

Abstract

PURPOSE We examine the performance of pure model-based iterative reconstruction with reduced-dose CT in follow-up of patients with early-stage testicular cancer. METHODS Sixteen patients (mean age 35.6 ± 7.4 years) with stage I or II testicular cancer underwent conventional dose (CD) and low-dose (LD) CT acquisition during CT surveillance. LD data was reconstructed with model-based iterative reconstruction (LD-MBIR). Datasets were objectively and subjectively analysed at 8 anatomical levels. Two blinded clinical reads were compared to gold-standard assessment for diagnostic accuracy. RESULTS Mean radiation dose reduction of 67.1% was recorded. Mean dose measurements for LD-MBIR were: thorax - 66 ± 11 mGy cm (DLP), 1.0 ± 0.2 mSv (ED), 2.0 ± 0.4 mGy (SSDE); abdominopelvic - 128 ± 38 mGy cm (DLP), 1.9 ± 0.6 mSv (ED), 3.0 ± 0.6 mGy (SSDE). Objective noise and signal-to-noise ratio values were comparable between the CD and LD-MBIR images. LD-MBIR images were superior (p < 0.001) with regard to subjective noise, streak artefact, 2-plane contrast resolution, 2-plane spatial resolution and diagnostic acceptability. All patients were correctly categorised as positive, indeterminate or negative for metastatic disease by 2 readers on LD-MBIR and CD datasets. CONCLUSIONS MBIR facilitated a 67% reduction in radiation dose whilst producing images that were comparable or superior to conventional dose studies without loss of diagnostic utility.

DOI: 10.1016/j.ejro.2016.01.002
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@article{Murphy2016FeasibilityOL, title={Feasibility of low-dose CT with model-based iterative image reconstruction in follow-up of patients with testicular cancer.}, author={Kevin P Murphy and Lee Crush and Siobhan B O'Neill and James Foody and Miche{\'a}l Breen and Adrian Brady and Paul J Kelly and Derek G Power and Paul Sweeney and Jackie Bye and Owen J O'Connor and Michael M Maher and Kevin N O'Regan}, journal={European journal of radiology open}, year={2016}, volume={3}, pages={38-45} }