A novel alternative to classify tissues from T sub(1) and T sub(2) relaxation times for prostate MRI

To segment and classify the different attenuation regions from MRI at the pelvis level using the T sub(1) and T sub(2) relaxation times and anatomical knowledge as a first step towards the creation of PET/MR attenuation maps. Relaxation times were calculated by fitting the pixel-wise intensities of...

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Bibliographic Details
Published in:Magma (New York, N.Y.) N.Y.), 2016-10, Vol.29 (5), p.777-788
Main Authors: Bojorquez, Jorge Zavala, Bricq, Stephanie, Brunotte, Francois, Walker, Paul M, Lalande, Alain
Format: Article
Language:English
Subjects:
Attenuation
Bones
Classification
Magnetic resonance imaging
Muscles
Positron emission
Prostate
Relaxation time
Online Access:Get full text
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Summary:To segment and classify the different attenuation regions from MRI at the pelvis level using the T sub(1) and T sub(2) relaxation times and anatomical knowledge as a first step towards the creation of PET/MR attenuation maps. Relaxation times were calculated by fitting the pixel-wise intensities of acquired T sub(1)- and T sub(2)-weighted images from eight men with inversion-recovery and multi-echo multi-slice spin-echo sequences. A decision binary tree based on relaxation times was implemented to segment and classify fat, muscle, prostate, and air (within the body). Connected component analysis and an anatomical knowledge-based procedure were implemented to localize the background and bone. Relaxation times at 3 T are reported for fat (T sub(1) = 385 ms, T sub(2) = 121 ms), muscle (T sub(1) = 1295 ms, T sub(2) = 40 ms), and prostate (T sub(1) = 1700 ms, T sub(2) = 80 ms). The relaxation times allowed the segmentation-classification of fat, prostate, muscle, and air, and combined with anatomical knowledge, they allowed classification of bone. The good segmentation-classification of prostate [mean Dice similarity score (mDSC) = 0.70] suggests a viable implementation in oncology and that of fat (mDSC = 0.99), muscle (mDSC = 0.99), and bone (mDSCs = 0.78) advocates for its implementation in PET/MR attenuation correction. Our method allows the segmentation and classification of the attenuation-relevant structures required for the generation of the attenuation map of PET/MR systems in prostate imaging: air, background, bone, fat, muscle, and prostate.
ISSN:0968-5243
1352-8661
DOI:10.1007/s10334-016-0562-3