Changwei Ding, Presenter: Nothing to Disclose

Xiao Mei Lu MMed, Abstract Co-Author: Employee, Koninklijke Philips NV

Ping Wang MD, MS, Abstract Co-Author: Nothing to Disclose

Qiyong Guo MD, Abstract Co-Author: Nothing to Disclose

To investigate the ability of low dose parotid CT scan using an iterative model reconstruction (IMR) algorithm to detect the distinctive adipose tissue deposition in Sjögren’s syndrome. 

Eighteen patients with confirmed Sjögren’s syndrome were scanned using a 256-slice CT for visualization of the parotid gland. This protocol was approved by hospital ethics committee and written informed consent was obtained from each patient. Among these patients, five underwent routine dose scan (120 kV and 200 mAs) and filtered back projection algorithm was used for image reconstruction (RD-FBP group), and thirteen patients under low dose scan (80 kV, 200 mAs, 71% dose reduction), and iDose4 (level 5) and IMR (level 1) algorithm was used respectively for image reconstruction (LD-iDose4 group and LD-IMR group, respectively). The image noise (measureed in semispinalis capitis) was compared between RD-FBP group and LD-iDose4 and LD-IMR group. The images of LD-iDose4 group and LD-IMR group were read blinded by two experienced radiologists in consent for evaluation of the adipose tissue deposition in the parotid gland according to these features: detectability, interface contrast to parotid parenchyma, and density contrast to parotid parenchyma [1 (poor) to 5 (excellent)].

The image noise in the LD-IMR group was significantly lower than in the LD-iDose4 and RD-FBP groups (4.36±0.96, 6.92±1.11, and 5.77±1.44, respectively, P<0.05). There was no significant difference in the detectability of adipose tissue between LD-IMR and LD-iDose4 groups (P>0.05). The LD-IMR group displayed clearer boundary between adipose tissue and parotid parenchyma and offers higher density contrast than the LD-iDose4 group (P < 0.05).  

IMR algorithm reduced the noise of low dose parotid CT scan, even lower than RD-FBP, increased the interface and density contrast of adipose tissue and parotid parenchyma, so offered stronger ability to detect adipose tissue deposition in the parotid gland of patients with Sjögren’s syndrome.

IMR can improve the image quality of low dose CT scan, increase the contrast resolution between different tissues, and thereby enhance the ability to detect lesions. 

Ding, C, Lu, X, Wang, P, Guo, Q, Iterative Model Reconstruction Algorithm in Low kVp (80) Parotid CT Scan for Visualization of Adipose Tissue Deposition in Sjögren’s Syndrome.  Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, - ,Chicago IL. http://archive.rsna.org/2014/14012834.html