2021年10月25日

主题添加到邮件提醒收到一封电子邮件在发布新文章时请提供您的电子邮件地址来接收电子邮件当张贴新文章。请稍后再试。如果你继续这个问题请联系customerservice@slackinc.com。回到Healio gacvs对甲状腺影像报告和数据系统超声检查得分后分子分析是一个具有成本效益的选择协助不定甲状腺结节术前诊断,从回顾性研究显示数据。不确定甲状腺结节——那些细胞病理学分为贝塞斯达三世的规模我VI -挑战”来形容没有诊断手术,马蒂·镀金,面交(荣誉),博士,FRACP,皇家北岸医院的内分泌学家,悉尼,悉尼大学和高级讲师医学,在临床内分泌学和他的同事写道。辅助策略,如分子分析,机器学习模型和超声评分与甲状腺显像报告和数据系统(TI拉德)应承担的评分系统,可以帮助相应分类;然而,需要进一步的细化,以防止不必要的手术和增加积极的预测值。镀金是在悉尼皇家北岸医院的内分泌学家,和悉尼大学高级讲师。“我们可以更个性化的方法适用于遵循不确定甲状腺结节根据TI-RADS分数和患者的年龄,而不是一个通用的重复活检在3个月内,指南建议,“镀金告诉Healio。“这项研究表明,小说radiomic和放射策略可以用来协助不定的术前诊断甲状腺结节。” Re-stratifying risk In a retrospective review, Gild and colleagues analyzed data from 88 patients with Bethesda III nodules who went on to have diagnostic surgery between 2014 and 2019 with final pathological diagnosis (mean age, 60 years). Histology from the malignant nodules included 20 classified as papillary thyroid cancer, one as insular carcinoma, seven as follicular thyroid cancer, three Hurthle cell cancers and three classified as other. Each nodule was retrospectively scored through TI‐RADS, and two deep learning models were tested. One, ThyNet, was previously developed and trained on another data set, mainly containing determinate cases; a second model trained and was tested on the indeterminate cases reviewed by the researchers. Within the cohort, the mean TI‐RADS score was 3 for benign and 4 for malignant nodules (P = .0022). Researchers stratified nodules as radiological high risk (TI‐RADS 4 or 5) and low risk (TI‐RADS 2 or 3). The positive predictive value for the high radiological risk category among patients with nodules greater than 10 mm (n = 44) was 85% (95% CI, 70-93). The negative predictive value for low radiological risk in patients aged at least 60 years was 100% (95% CI, 83-100). “Older patients with indeterminate nodules may be reassured that the likelihood of a final malignant pathology is low, and they may feel more confident in observation rather than diagnostic surgery,” Gild told Healio. The researchers noted molecular testing is costly, often not subsidized and not easily accessible to those in less resourced countries; using the validated TI‐RADS score to re-stratify risk is a “simple, cost-neutral first‐line approach.” “In a cohort of suspicious lesions from molecular analysis, returning to TI‐RADS grade may assist with triage and surgical timing,” the researchers wrote. More machine learning data needed The area under the curve value of the novel classifier was 0.75 (95% CI, 0.62-0.84) and differed significantly from the chance‐level (P < .00001), according to the researchers. Gild said additional analyses with larger data sets may yield more meaningful findings regarding the utility of machine learning in predicting nodule malignancy. “The AUC through the deep learning models designed here were not high enough to be clinically meaningful; however, these methods are novel,” Gild told Healio. “Further refinement and larger data sets may assist in characterization of these nodules prior to surgery.” For more information: