Objectives: To evaluate the diagnostic performance of brain CT images reconstructed with a model-based iterative algorithm performed at usual and reduced dose.
Methods: 115 patients with histologically proven lung cancer were prospectively included over 15 months. Patients underwent two CT acquisitions at the initial staging, performed on a 256-slice MDCT, at standard (CTDIvol: 41.4 mGy) and half dose (CTDIvol: 20.7 mGy). Both image datasets were reconstructed with filtered back projection (FBP) and iterative model-based reconstruction (IMR) algorithms. Brain MRI was considered as the reference. Two blinded independent readers analysed the images.
Results: Ninety-three patients underwent all examinations. At the standard dose, eight patients presented 17 and 15 lesions on IMR and FBP CT images, respectively. At half-dose, seven patients presented 15 and 13 lesions on IMR and FBP CT images, respectively. The test could not highlight any significant difference between the standard dose IMR and the half-dose FBP techniques (p-value = 0.12). MRI showed 46 metastases on 11 patients. Specificity, negative and positive predictive values were calculated (98.9-100 %, 93.6-94.6 %, 75-100 %, respectively, for all CT techniques).
Conclusion: No significant difference could be demonstrated between the two CT reconstruction techniques.
Key Points: • No significant difference between IMR100 and FBP50 was shown. • Compared to FBP, IMR increased the image quality without diagnostic impairment. • A 50 % dose reduction combined with IMR reconstructions could be achieved. • Brain MRI remains the best tool in lung cancer staging.
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http://dx.doi.org/10.1007/s00330-017-5021-7 | DOI Listing |
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