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Model-based iterative reconstruction and adaptive statistical iterative reconstruction techniques in abdominal CT: comparison of image quality in the detection of colorectal liver metastases.

PURPOSE
To prospectively evaluate dose reduction and image quality characteristics of abdominal computed tomographic (CT) scans reconstructed with model-based iterative reconstruction (MBIR) compared with adaptive statistical iterative reconstruction (ASIR) in oncology patients with colorectal liver metastases.


MATERIALS AND METHODS
The study complied with HIPAA guidelines and was approved by the ethics committee of the institutional review board. All patients gave written informed consent. Fifty-one patients with colorectal liver metastases underwent body CT (thorax and abdomen) with a 64-section multidetector unit. With a radiation dose reduction by 2.36 mGy compared to standard of care CT with ASIR 50% (radiation dose, 7.54 mGy), MBIR can provide diagnostically acceptable CT scans without compromising image quality. Two radiologists independently assessed randomized images in a blinded manner. Imaging sets were compared for lesion detection, lesion conspicuity, overall image quality, and signal-to-noise ratio with a paired sample t test. Inter- and intraobserver agreement was assessed with the Cohen κ.


RESULTS
The mean volume CT dose index was 5.18 mGy ± 0.76, mean dose-length product 374 mGy · cm ± 63.47, mean effective diameter 29.38 cm ± 3.46, and mean size-specific dose estimate 6.52 mGy ± 0.73. In small liver lesions (<10 mm), detection and conspicuity were significantly higher with MBIR than with ASIR for both right (t = 3.245, P = .004 and t = 2.696, P = .013, respectively) and left (t = 2.390, P = .038 and t = 2.283, P = .046) liver lobes. Subjective image noise (t = 4.506, P < .001), artifacts (t = 3.479, P = .001), and diagnostic confidence (t = 2.643, P = .011) were significantly better with MBIR than with ASIR.


CONCLUSION
MBIR performed better than ASIR 50% at providing diagnostically acceptable CT scans without compromising image quality and in the detection of colorectal liver metastases.