Degroote Lucas W, Rodewald Paul G
School of Environment and Natural Resources, The Ohio State University, 210 Kottman Hall, 2021 Coffey Rd, Columbus, Ohio 43210, USA.
J Wildl Dis. 2008 Apr;44(2):446-50. doi: 10.7589/0090-3558-44.2.446.
Intensity of hematozoan infection is infrequently quantified because accurate calculations require visual counts of parasites relative to a large number of erythrocytes. Manual quantification of erythrocytes can be circumvented by using ImageJ software (developed by the National Institutes of Health) to count erythrocyte nuclei from digital images. Here we use the ratio of microscope erythrocyte counts to digital image erythrocyte counts (field:image ratio) to extrapolate erythrocyte counts from smaller digital images to the microscope's larger field of view. Field:image ratios were consistently calculated from 10 slides (resampling P = 0.049) and used to rapidly estimate intensity of infection within 50,000 or more erythrocytes. Intensity of hematozoan infection calculated from manual quantification of 2,000 erythrocytes was significantly lower (0.46 times) than intensity calculated from digital quantification of 50,000 erythrocytes (bootstrap P = 0.02). We contend that digital quantification of hematozoan infection offers a rapid and precise method to quantify infections of low to moderate intensity.
血寄生虫感染强度很少被量化，因为准确计算需要相对于大量红细胞对寄生虫进行目视计数。使用ImageJ软件（由美国国立卫生研究院开发）从数字图像中计数红细胞核，可以避免手动对红细胞进行量化。在这里，我们使用显微镜下红细胞计数与数字图像红细胞计数的比率（视野：图像比率），将较小数字图像中的红细胞计数外推到显微镜的较大视野。从10张载玻片上持续计算视野：图像比率（重采样P = 0.049），并用于快速估计50000个或更多红细胞内的感染强度。通过手动对2000个红细胞进行量化计算出的血寄生虫感染强度，显著低于通过对50000个红细胞进行数字量化计算出的强度（自展检验P = 0.02），前者仅为后者的0.46倍。我们认为，血寄生虫感染的数字量化提供了一种快速且精确的方法来量化低至中等强度的感染。
