Detection of CBF deficits in neuropsychiatric disorders by an expert system: a 99Tcm-HMPAO brain SPET study using automated image registration.
Detection of CBF deficits in neuropsychiatric disorders by an expert system: a 99Tcm-HMPAO brain SPET study using automated image registration.
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通过专家系统检测神经精神疾病中的 CBF 缺陷：使用自动图像配准的 99Tcm-HMPAO 大脑 SPET 研究。
DOI：
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发表时间：
1999
影响因子：
1.5
通讯作者：
H. Fukuda
中科院分区：
文献类型：
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作者：
M. Imran;R. Kawashima;K. Sato;S. Kinomura;S. Ono;A. Qureshy;H. Fukuda
本研究的目的是开发一种客观的方法，使用统计图像分析协议评估rCBF赤字，并验证其在临床实践中的有效使用。本文对40例正常人、10例Alzheimer病和10例抑郁症患者进行了99 Tcm-HMPAO脑SPET显像。自动图像配准用于标准化所有受试者的大脑结构的大小和形状。前30名正常人的图像用于构建正常数据库。将另外10例正常人和20例患者的CBF图像逐体素与正常数据库进行比较，通过统计学评价来映射CBF异常。并与临床报道的CBF图像进行比较。专家系统检测到核医生报告的所有rCBF缺陷。专家系统还确定了一些具有特殊信息的其他区域，如萎缩和双侧不对称。我们的结论是，这个专家系统可以描绘CBF赤字具有足够高的准确性，区分正常与异常CBF图像使用基于体素的比较。专家系统的使用改善了rCBF SPET图像评价。
The aims of this study were to develop an objective method for assessing rCBF deficits using a statistical image analysis protocol and to validate its effective use in clinical practice. 99Tcm-HMPAO brain SPET images were acquired for 40 normal subjects, 10 patients with Alzheimer's disease and 10 patients with depression. Automated image registration was used to standardize the size and shape of the brain structures for all subjects. The images of the first 30 normal subjects were used to construct a normal database. The CBF images of the other 10 normal subjects and the 20 patients were compared voxel by voxel with the normal database to map CBF abnormalities by statistical evaluation. The results were compared with the clinical reports of CBF images. The expert system detected all rCBF deficits reported by the nuclear physicians. Some additional areas with special information, like atrophy and bilateral asymmetry, were also identified by the expert system. We conclude that this expert system can delineate CBF deficits with sufficiently high accuracy, differentiating normal from abnormal CBF images using voxel-based comparisons. The use of an expert system improves rCBF SPET image evaluation.