Postoperative low-dose follow-up computed tomography for patients with stomach cancer: optimal blending ratio of adaptive statistical iterative reconstruction for image quality and diagnostic performance.

Abstract:

OBJECTIVE:To compare the diagnostic performance of adaptive statistical iterative reconstruction applied low-dose computed tomography (CT) (LDCT) with that of the standard-dose CT (SDCT) for local recurrence in patients with stomach cancer. METHODS:Seventy-nine consecutive patients who had undergone surgical resection for stomach cancer were enrolled. To monitor recurrence, SDCT (120 kilovolt peak [kVp], 200mAs) had been performed. The LDCT (120 kVp, 100 mA s) was taken, and images were reconstructed with 4 levels of adaptive statistical iterative reconstruction (ASIR) blending (0%, 30%, 50%, and 70%). Two blinded radiologists recorded the diagnostic confidence scores for local recurrence in each data set using a 5-point scale. Endoscopic biopsy results served as the reference standard. Receiver operating characteristic (ROC) curve analysis was used to calculate the diagnostic performance. RESULTS:The diagnostic performance of LDCT with variable ASIR blending ratios was comparable to that of SDCT (area under ROC curve, 0.727-0.734, 0.687, respectively, P > 0.05). CONCLUSIONS:The diagnostic performance of ASIR applied LDCT is comparable to that of SDCT.

journal_name

J Comput Assist Tomogr

authors

Shim HS,Kim SH,Yoon JH,Lim YJ,Kim OH,Ryu JH,Eun CK

doi

10.1097/RCT.0000000000000057

subject

Has Abstract

pub_date

2014-05-01 00:00:00

pages

376-82

issue

3

eissn

0363-8715

issn

1532-3145

journal_volume

38

pub_type

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