Literature DB >> 20718916

Fusion of high b-value diffusion-weighted and T2-weighted MR images improves identification of lymph nodes in the pelvis.

N Mir1, S A Sohaib, D Collins, D M Koh.   

Abstract

Accurate identification of lymph nodes facilitates nodal assessment by size, morphological or MR lymphographic criteria. We compared the MR detection of lymph nodes in patients with pelvic cancers using T2-weighted imaging, and fusion of diffusion-weighted imaging (DWI) and T2-weighted imaging. Twenty patients with pelvic tumours underwent 5-mm axial T2-weighted and DWI (b-values 0-750 s/mm(2)) on a 1.5T system. Fusion images of b = 750 s/mm(2) diffusion-weighted MR and T2-weighted images were created. Two radiologists evaluated in consensus the T2-weighted images and fusion images independently. For each image set, the location and diameter of pelvic nodes were recorded, and nodal visibility was scored using a 4-point scale (0-3). Nodal visualisation was compared using Relative to an Identified Distribution (RIDIT) analysis. The mean RIDIT score describes the probability that a randomly selected node will be better visualised relative to the other image set. One hundred fourteen pelvic nodes (mean 5.9 mm; 2-10 mm) were identified on T2-weighted images and 161 nodes (mean 4.3 mm; 2-10 mm) on fusion images. Using fusion images, 47 additional nodes were detected compared with T2-weighted images alone (eight external iliac, 24 inguinal, 12 obturator, two peri-rectal, one presacral). Nodes detected only on fusion images were 2-9 mm (mean 3.7 mm). Nodal visualisation was better using fusion images compared with T2-weighted images (mean RIDIT score 0.689 vs 0.302). Fusion of diffusion-weighted MR with T2-weighted images improves identification of pelvic lymph nodes compared with T2-weighted images alone. The improved nodal identification may aid treatment planning and further nodal characterisation.

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Year:  2010        PMID: 20718916     DOI: 10.1111/j.1754-9485.2010.02182.x

Source DB:  PubMed          Journal:  J Med Imaging Radiat Oncol        ISSN: 1754-9477            Impact factor:   1.735


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