前列腺磁共振成像中的椭圆形公式可靠吗?

Current health sciences journal Pub Date : 2023-10-01 Epub Date: 2023-12-29 DOI:10.12865/CHSJ.49.04.8
Rossy Vlăduț Teică, Cristina Mihaela Ciofiac, Lucian Mihai Florescu, Ioana-Andreea Gheonea
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引用次数: 0

摘要

我们的研究旨在研究椭圆公式在不同尺寸前列腺 MRI 中的准确性,并确定其使用范围。研究对象包括31名前列腺囊显像清晰、完整的患者,其中不包括恶性转化的前列腺和经过治疗的前列腺(前列腺囊与实质之间的对比度降低)。根据椭圆公式重新计算了每位患者的前列腺体积,然后与分割法计算出的前列腺体积进行比较。两种方法计算出的前列腺体积相似,在某些情况下几乎完全相同,但有轻微的低估倾向,100 立方厘米以下的前列腺体积共有 18 例,平均低估了 7.6%(+/-6%),体积超过 100 立方厘米的前列腺体积共有 13 例,平均高估了 3.2%(+/-2.5%),其中有 4 例两种公式的差异低于 1%。两个变量之间没有统计学差异,学生 t 检验 p 值=0.039。椭圆公式的精确度为 92% (+/-6%),在正确执行时可以认为是准确的,但如果我们考虑到 PSA 密度在诊断、治疗和随访中的重要性,当椭圆公式返回的值接近临界值时,可以通过分割方法或高精度软件计算次要值。
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Is the Ellipsoid Formula Reliable in Prostate MRI?

Our study seeks to study the accuracy of the ellipsoidal formula in prostate MRI of different sizes and to establish the limits of its use. The study included 31 patients with a well-visualized, intact prostatic capsule, excluding malignantly transformed prostates, as well as treated prostates, in which the contrast between the prostatic capsule and parenchyma is reduced. Each patient's prostatic volume was recalculated according to the ellipsoidal formula, and then it was compared with the prostatic volume calculated by the segmentation method. The two calculated volumes were similar, in some cases almost identical, with a slight tendency to underestimate prostate volume below 100cm3, in total in 18 cases, on average by 7.6% (+/-6%), overestimation of those with a volume over 100cm3, a total of 13 cases, on average by 3.2% (+/-2.5%), and of all, in 4 cases the difference between the two formulas was below 1%. There was no statistical difference between the two variables, Student's t-test p-value=0.039. With a precision of 92% (+/-6%), the ellipsoidal formula can be considered accurate when it is correctly performed, but if we take into account the importance that PSA density is starting to have in diagnosis, treatment and follow-up, the calculation of a secondary value through the segmentation method or high-precision software can be motivated when the ellipsoidal formula returns a value close to a threshold.

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