Analyzing attributes of vessel populations

被引:62
作者
Bullitt, E
Muller, KE
Jung, IY
Lin, WL
Aylward, S
机构
[1] Univ N Carolina, Div Neurosurg, CH, Chapel Hill, NC 27599 USA
[2] Univ N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA
[3] Univ N Carolina, Dept Radiol, Chapel Hill, NC 27599 USA
关键词
magnetic resonance angiography; cerebral blood vessels; tortuosity; segmentation; morphology; vessel trees;
D O I
10.1016/j.media.2004.06.024
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Almost all diseases affect blood vessel attributes (vessel number, radius, tortuosity, and branching pattern). Quantitative measurement of vessel attributes over relevant vessel populations could thus provide an important means of diagnosing and staging disease. Unfortunately, little is known about the statistical properties of vessel attributes. In particular, it is unclear whether vessel attributes fit a Gaussian distribution, how dependent these values are upon anatomical location, and how best to represent the attribute values of the multiple vessels comprising a population of interest in a single patient. The purpose of this report is to explore the distributions of several vessel attributes over vessel populations located in different parts of the head. In 13 healthy subjects, we extract vessels from MRA data, define vessel trees comprising the anterior cerebral, right and left middle cerebral, and posterior cerebral circulations, and, for each of these four populations, analyze the vessel number, average radius, branching frequency, and tortuosity. For the parameters analyzed, we conclude that statistical methods employing summary measures for each attribute within each region of interest for each patient are preferable to methods that deal with individual vessels, that the distributions of the summary measures are indeed Gaussian, and that attribute values may differ by anatomical location. These results should be useful in designing studies that compare patients with suspected disease to a database of healthy subjects and are relevant to groups interested in atlas formation and in the statistics of tubular objects. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:39 / 49
页数:11
相关论文
共 42 条
[1]  
[Anonymous], 2002, HORIZONS CANC THER
[2]   Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction [J].
Aylward, SR ;
Bullitt, E .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2002, 21 (02) :61-75
[3]  
Baish JW, 2000, CANCER RES, V60, P3683
[5]   A technique for quantitative three-dimensional analysis of microvascular structure [J].
Brey, EM ;
King, TW ;
Johnston, C ;
McIntire, LV ;
Reece, GP ;
Patrick, CW .
MICROVASCULAR RESEARCH, 2002, 63 (03) :279-294
[6]  
Bullitt E, 2003, LECT NOTES COMPUT SC, V2878, P671
[7]   Measuring tortuosity of the intracerebral vasculature from MRA images [J].
Bullitt, E ;
Gerig, G ;
Pizer, SM ;
Lin, WL ;
Aylward, SR .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2003, 22 (09) :1163-1171
[8]   Symbolic description of intracerebral vessels segmented from magnetic resonance angiograms and evaluation by comparison with X-ray angiograms [J].
Bullitt, E ;
Aylward, S ;
Smith, K ;
Mukherji, S ;
Jiroutek, M ;
Muller, K .
MEDICAL IMAGE ANALYSIS, 2001, 5 (02) :157-169
[9]  
BULLITT E, 2004, INPRESS MICCAI LECT
[10]  
Burger P.C., 1991, SURG PATHOLOGY NERVO