Erdi Y E, Humm J L, Imbriaco M, Yeung H, Larson S M
Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA.
J Nucl Med. 1997 Sep;38(9):1401-6.
Preliminary evidence indicates that the fraction of bone containing metastatic lesions is a strong prognostic indicator of survival longevity for prostate and breast cancer. Our current approach to quantify metastatic bone lesions, called the Bone Scan Index, is based on an inspection of the bone scan, estimating visually the fraction of each bone involved and then summing across all bones to determine the percentage of total skeletal involvement. This approach, however, is time consuming, subjective and dependent on individual interpretation.
To overcome these problems, a semiautomated image segmentation program was developed for the quantitation of metastases from planar whole-body bone scans. The user is required to insert a seed point into each metastatic region on the image. The algorithm then connects pixels to the seed pixel in all directions until a contrast-dependent threshold is reached. The optimal threshold for cessation of the region growing is determined from phantom studies. On the images, lesion delineation and size measurements were performed by the algorithm. Each delineated lesion is associated with a bone site using pull-down menus. The program then computes the fraction of lesion involvement in each bone based on look-up-tables containing the relationship of bone mass with race, sex, height and age. These look-up-tables were obtained by multiple regression of the skeletal mass measurements in humans. The total fraction of skeletal involvement is then obtained from the individual fractional masses. For individual fractional mass, values given in International Commission on Radiation Protection Publication No. 23 were used.
The bone metastases analysis system has been used on 11 scans from 6 patients. The correlation was high (r = 0.83) between conventional (manually drawn region-of-interest) and this analysis system. Bone metastases analysis results in consistently lower estimates of fractional involvement in bone compared with the conventional region-of-interest drawing or visual estimation method. This is due to the apparent broadening of objects at and below the limits of resolution of the gamma camera.
Image segmentation reduces the delineation and quantitation time of lesions by at least two compared with manual region-of-interest drawing. The objectivity of this technique allows the detection of small variations in follow-up patient scans for which the manual region-of-interest method may fail, due to performance variability of the user. This method preserves the diagnostic skills of the nuclear medicine physician to select which bony structures contain lesions, yet combines it with an objective delineation of the lesion.
初步证据表明，含有转移病灶的骨部分是前列腺癌和乳腺癌生存寿命的一个强有力的预后指标。我们目前用于量化转移性骨病灶的方法，称为骨扫描指数，是基于对骨扫描的检查，通过视觉估计每块骨受累的部分，然后对所有骨进行求和以确定全身骨骼受累的百分比。然而，这种方法耗时、主观且依赖于个人解读。
为克服这些问题，开发了一种半自动图像分割程序，用于从平面全身骨扫描中定量转移灶。要求用户在图像上的每个转移区域插入一个种子点。然后算法将像素在所有方向上连接到种子像素，直到达到对比度相关的阈值。从体模研究中确定区域生长停止的最佳阈值。在图像上，由算法进行病灶勾勒和大小测量。使用下拉菜单将每个勾勒出的病灶与一个骨部位相关联。然后该程序根据包含骨质量与种族、性别、身高和年龄关系的查找表计算每个骨中病灶受累的部分。这些查找表是通过对人类骨骼质量测量进行多元回归获得的。然后从各个部分质量中获得全身受累的总部分。对于个体部分质量，使用国际辐射防护委员会第23号出版物给出的值。
骨转移分析系统已应用于6例患者的11次扫描。传统方法（手动绘制感兴趣区域）与该分析系统之间的相关性很高（r = 0.83）。与传统感兴趣区域绘制或视觉估计方法相比，骨转移分析结果在骨受累部分的估计上始终较低。这是由于γ相机分辨率极限及以下的物体明显变宽所致。
与手动绘制感兴趣区域相比，图像分割将病灶勾勒和定量时间至少缩短了两倍。该技术的客观性使得能够检测出随访患者扫描中的微小差异，而手动感兴趣区域方法可能因用户表现的变异性而无法检测到这些差异。这种方法保留了核医学医师选择哪些骨结构包含病灶的诊断技能，同时将其与病灶的客观勾勒相结合。
