A novel alternative to classify tissues from T 1 and T 2 relaxation times for prostate MRI
A novel alternative to classify tissues from T 1 and T 2 relaxation times for prostate MRI
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DOI：
10.1007/s10334-016-0562-3
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发表时间：
2016-10-01
影响因子：
2.3
通讯作者：
Lalande, Alain
中科院分区：
文献类型：
--
作者：
Bojorquez, Jorge Zavala;Bricq, Stephanie;Lalande, Alain
为了利用T（1）和T（2）弛豫时间和解剖学知识在骨盆水平对MRI的不同衰减区域进行分割和分类，作为创建PET/MR衰减图的第一步。通过拟合获得的8名男性的T（1）和T（2）加权图像的像素级强度来计算弛豫时间，这些图像来自反转恢复和多回波多层自旋回波成像。回波序列基于松弛时间的决策二叉树被实现以分割和分类脂肪、肌肉、前列腺和空气（在身体内）。在3 T下，脂肪（T（1）= 385 ms，T（2）= 121 ms）、肌肉（T（1）= 1295 ms，T（2）= 40 ms）和前列腺（T（1）= 1700 ms，T（2）= 80 ms）的弛豫时间被报告。弛豫时间允许脂肪、前列腺、肌肉和空气的分割分类，并且结合解剖学知识，它们允许骨骼的分类。前列腺的良好分割分类[平均Dice相似性评分（mDSC）= 0.70]表明在肿瘤学和脂肪学中的可行实施（mDSC = 0.99），肌肉（mDSC = 0.99），和骨（mDSCs = 0.78）主张在PET/MR衰减校正中实施该方法。在前列腺成像中生成PET/MR系统衰减图所需的相关结构：空气、背景、骨骼、脂肪、肌肉和前列腺。
To segment and classify the different attenuation regions from MRI at the pelvis level using the T (1) and T (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 (1)- and T (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 (1) = 385 ms, T (2) = 121 ms), muscle (T (1) = 1295 ms, T (2) = 40 ms), and prostate (T (1) = 1700 ms, T (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.