甲状旁腺重量估计:超出椭球体体积。

IF 3 3区 医学 Q2 ENDOCRINOLOGY & METABOLISM
Haley Corbin, Nathalia Josette Roth, Linwah Yip, Sally E Carty, Raja R Seethala
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引用次数: 0

摘要

目的:甲状旁腺重量是一种简单、可靠的功能状态指标,是总/术中评估的基础,尽管有时难以获得。我们评估模型来估计重量从尺寸和创建一个在线计算器。方法:前瞻性收集76例(4 / 6/2023)患者124个甲状旁腺(111个高细胞,13个正常细胞)的实际重量(AW)、细胞结构、腺体特征和大小。简单体积重量估计(VWE):椭球,荚膜,新型荚膜,和盒子形状比较AW。多元线性回归(MLR)通过内部(k-fold)验证和外部验证对档案队列(263个腺瘤,2016-2022)进行验证。外科医生的体重估计、血清值和使用QuPath表面积工具测量的显微表面积的子集与AW相关。结果:最优MLR模型包括囊体VWE、细胞度和菌体特性(R2:0.92, p 2: 0.89, p 2: 0.86,标准化均方根误差(nRMSE): 0.058)。有趣的是,在这个子集中,外科医生的体重估计(n = 31)更有利(R2: 0.97, nRMSE: 0.087)。QuPath辅助的基于表面积的重量估计与AW的相关性较弱。AW、CWE和大小与血清值均无明显相关性。结论:在线计算器模拟囊体VWE和细胞结构是预测AW的良好指标。生产部门测量的方差很重要,但建模是不切实际的。外科医生的估计相当准确,强调了这项技能的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parathyroid weight estimation: beyond ellipsoid volume.

Purpose: Parathyroid weight is a simple, robust functional status indicator and cornerstone of gross/intraoperative assessment, though sometimes unobtainable. We evaluate models to estimate weight from size and create an online calculator.

Methods: Actual weights (AW), cellularity, prosector identity and size were prospectively collected for 124 parathyroids (111 hypercellular, 13 normocellular) in 76 patients (4-6/2023). Simple volumetric weight estimates (VWE) for: ellipsoid, capsular, the novel capsuloid, and box shapes were compared with AW. Multiple linear regression (MLR) was performed with internal (k-fold) validation and external validation on an archival cohort (263 adenomas, 2016-2022). Subsets with surgeon's weight estimates, serum values, and microscopic surface area measured using the QuPath surface area tool were correlated with AW.

Results: The optimal MLR model included capsuloid VWE, cellularity, and prosector identity (R2:0.92, p < 0.0001). A more generalizable model without including prosector identity (R2: 0.89, p < 0.0001) was used for the online calculator weight estimate (CWE). The calculator was a good predictor of AW on the adenoma dataset (R2: 0.86, normalized root mean squared error (nRMSE): 0.058). Interestingly, the surgeon's weight estimate (n = 31) was more favorable (R2: 0.97, nRMSE: 0.087) in this subset. QuPath assisted surface area-based weight estimates showed weaker correlation with AW. Neither AW, CWE, nor size correlated strongly with serum values.

Conclusion: An online calculator modeling capsuloid VWE and cellularity is a good predictor of AW. Variance in prosector measurements is important but impractical to model. Surgeon's estimates were quite accurate, emphasizing the value of this skill.

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来源期刊
Endocrine
Endocrine ENDOCRINOLOGY & METABOLISM-
CiteScore
6.50
自引率
5.40%
发文量
295
审稿时长
1.5 months
期刊介绍: Well-established as a major journal in today’s rapidly advancing experimental and clinical research areas, Endocrine publishes original articles devoted to basic (including molecular, cellular and physiological studies), translational and clinical research in all the different fields of endocrinology and metabolism. Articles will be accepted based on peer-reviews, priority, and editorial decision. Invited reviews, mini-reviews and viewpoints on relevant pathophysiological and clinical topics, as well as Editorials on articles appearing in the Journal, are published. Unsolicited Editorials will be evaluated by the editorial team. Outcomes of scientific meetings, as well as guidelines and position statements, may be submitted. The Journal also considers special feature articles in the field of endocrine genetics and epigenetics, as well as articles devoted to novel methods and techniques in endocrinology. Endocrine covers controversial, clinical endocrine issues. Meta-analyses on endocrine and metabolic topics are also accepted. Descriptions of single clinical cases and/or small patients studies are not published unless of exceptional interest. However, reports of novel imaging studies and endocrine side effects in single patients may be considered. Research letters and letters to the editor related or unrelated to recently published articles can be submitted. Endocrine covers leading topics in endocrinology such as neuroendocrinology, pituitary and hypothalamic peptides, thyroid physiological and clinical aspects, bone and mineral metabolism and osteoporosis, obesity, lipid and energy metabolism and food intake control, insulin, Type 1 and Type 2 diabetes, hormones of male and female reproduction, adrenal diseases pediatric and geriatric endocrinology, endocrine hypertension and endocrine oncology.
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