Suppr超能文献

胚胎/胎儿剂量测定的最新解剖学数据和数学模型。

Updated anatomical data and mathematical models for embryo/fetus dosimetry.

作者信息

Mehta Suresh

机构信息

Department of Health Research, National Institute of Medical Statistics (ICMR), Ansari Nagar, New Delhi, India.

出版信息

Indian J Nucl Med. 2012 Apr;27(2):101-4. doi: 10.4103/0972-3919.110693.

Abstract

PURPOSE OF THE STUDY

It is proposed to fill in the gaps in the existing data matrix of mass/volume of uterus, its contents as well as mass of fetal organs by mathematical techniques down to 6 week gestation and relate this dynamic target mass during in-utero growth to recently revised Medical Internal Radiation Dose (MIRD) 21 schema.

MATERIALS AND METHODS

The existing data is subjected to numerical interpolations using a standard 4 degree polynomial for certain set of variables. Interpolations of mass, volume, etc., of various components of the uterus (placenta, embryo/fetus, brain, uterine wall, etc.) at weekly/biweekly intervals have been carried out. Subsequently, the step wise regression starting with three predictors - placental mass (Wp), total fetal mass (Wf) and greatest length (H) for the augmented data set led to identification of "H" and "Wf" as the most significant predictors for 10 fetal organ masses Wi using standard software "MS Excel".

RESULTS AND DISCUSSION

Further analysis utilizing allometric equations reveal that there is strong evidence in favor of Wf compared to H for predicting (P < 0.001) the individual organ mass "Wi". The prediction of Wi -liver, heart, thymus, pancreas, and thyroid fall under the linear case of prediction (predictor is ln [Wf]); whereas the brain, lung, kidney, spleen, crown-heel length, etc., fall under linear-quadratic case (where ln (Wf) plus ln (Wf)) are the predictors) respectively. The estimates indicate a rapid decline of "brain mass/total mass" ratio from 80% to 39% during 7-9 weeks. Information on specific absorbed fraction Φ (=φ/mT) is required to arrive at the dose estimates (φ being the absorbed fraction). The very small target mass mT-few milligrams (for 90% of organs) to a maximum 11 g for brain during early pregnancy; the fetal thyroid, with its mass variation of about 300% during 10-13 weeks can impact Φ. Reported standardized doses are presented and variation of Φ with source-target distance for individual specific scaling of Φ is discussed.

CONCLUSION

Time dependent mass m (t) of the target and consequently Φ(t) [=φ(t)/mT (t)] of the revised MIRD dose expression can be of relevance in fetal dosimetry when source-target distances are in reasonable limits.

摘要

研究目的

建议通过数学技术填补子宫质量/体积、其内容物以及胎儿器官质量的现有数据矩阵中的空白,直至妊娠6周,并将子宫内生长期间的这一动态目标质量与最近修订的医学内照射剂量(MIRD)21模式相关联。

材料与方法

对现有数据使用标准的4次多项式对特定变量集进行数值插值。已按每周/每两周的间隔对子宫各组成部分(胎盘、胚胎/胎儿、脑、子宫壁等)的质量、体积等进行插值。随后,以三个预测变量——胎盘质量(Wp)、胎儿总质量(Wf)和最大长度(H)作为增强数据集的起始变量,通过逐步回归,使用标准软件“MS Excel”确定“H”和“Wf”是10个胎儿器官质量Wi的最显著预测变量。

结果与讨论

利用异速生长方程的进一步分析表明,与H相比,有强有力的证据支持Wf可用于预测(P < 0.001)单个器官质量“Wi”。Wi(肝脏、心脏、胸腺、胰腺和甲状腺)的预测属于线性预测情况(预测变量为ln [Wf]);而脑、肺、肾、脾、顶臀长度等则属于线性 - 二次预测情况(预测变量为ln (Wf) 加上 [ln (Wf)]²)。估计结果表明,在7 - 9周期间,“脑质量/总质量”比从80%迅速下降至39%。需要特定吸收分数Φ(=φ/mT)的信息来得出剂量估计值(φ为吸收分数)。目标质量mT非常小——早期妊娠时,90%的器官为几毫克,脑最大为11克;胎儿甲状腺在10 - 13周期间质量变化约300%,会影响Φ。给出了报告的标准化剂量,并讨论了Φ随源 - 靶距离的变化情况,以便对Φ进行个体特定缩放。

结论

当源 - 靶距离在合理范围内时,目标的时间依赖性质量m (t) 以及因此修订后的MIRD剂量表达式中的Φ(t) [=φ(t)/mT (t)] 在胎儿剂量测定中可能具有相关性。

相似文献

3
Mathematical representation of organ growth in the human embryo/fetus.人类胚胎/胎儿器官生长的数学表示
Int J Biomed Comput. 1995 Jun;39(3):337-47. doi: 10.1016/0020-7101(95)01115-u.
6
The development of a phantom to determine foetal organ doses from 131I in the foetal thyroid.
Phys Med Biol. 2000 Sep;45(9):2583-91. doi: 10.1088/0031-9155/45/9/311.

本文引用的文献

8
Estimating the surface area of the human body.
Stat Med. 1996 Jul 15;15(13):1325-32. doi: 10.1002/(SICI)1097-0258(19960715)15:13<1325::AID-SIM233>3.0.CO;2-K.
10
Mathematical representation of organ growth in the human embryo/fetus.人类胚胎/胎儿器官生长的数学表示
Int J Biomed Comput. 1995 Jun;39(3):337-47. doi: 10.1016/0020-7101(95)01115-u.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验