肾上腺病变分类重新审视:双能CT衍生的虚拟非增强衰减阈值的验证和调整。

IF 2.3 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Pascale Bernard, Christian Nelles, Philipp Fervers, Joline Schwan, Kaloyan Dankov, David Maintz, David Zopfs, Nils Große Hokamp, Thorsten Persigehl, Simon Lennartz
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引用次数: 0

摘要

目的:双能CT (DECT)衍生的虚拟无增强(VUE)图像已被研究用于肾上腺病变的鉴别,但先前报道的阈值不同,阻碍了临床应用。我们的目的是在一个大型回顾性队列中测试以前的肾上腺病变分化的VUE阈值,根据我们的数据提供一个交叉验证的阈值,并研究潜在恶性肿瘤对分化准确性的影响。方法:290例348例肾上腺病变,其中转移169例,腺瘤179例。从先前的3项研究中检索双层dect衍生的VUE阈值,应用于我们的队列,并计算相应的敏感性/特异性/准确性。根据我们的数据,采用五重交叉验证的roc分析确定最佳阈值。此外,计算了与未增强图像中10 HU阈值具有相似特异性的阈值。根据潜在的恶性肿瘤进行肾上腺病变的亚组分析。结果:先前建议的阈值分别为20、22、29 HU,相应的灵敏度/特异度/准确度分别为0.61/0.92/0.76、0.67/0.91/0.78、0.82/0.59/0.71。从我们的队列中确定的阈值为24.7 HU,敏感性/特异性/准确性为0.76/0.81/0.79。疾病特异性亚组的分化表现出相似的敏感性/特异性/准确性(黑色素瘤:0.78/0.84/0.79;肺癌:0.78 / 0.8/0.78;碾压混凝土:0.78 / 1/0.79)。与未增强的10 HU临界值相似,达到0.98特异性的VUE阈值为17.3 HU,敏感性为0.49。结论:先前的VUE衰减阈值对腺瘤和转移瘤的鉴别准确度不同。交叉验证的VUE阈值为24.7 HU,平均准确率为0.79,而17.3 HU的阈值与未增强图像中10 HU阈值的特异性相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adrenal lesion classification revisited: validation and adjustment of dual-energy CT derived virtual unenhanced attenuation thresholds.

Objectives: Dual-energy CT (DECT)-derived virtual unenhanced (VUE) images have been investigated for adrenal lesion differentiation, yet previously reported thresholds vary, hampering clinical application. We aimed to test previous VUE thresholds for adrenal lesion differentiation in a large retrospective cohort, to provide a cross-validated threshold based on our data, and to investigate the influence of underlying malignancies on differentiation accuracy.

Methods: 290 patients with 348 adrenal lesions (169 metastases, 179 adenomas) were included. Dual-layer DECT-derived VUE thresholds from 3 previous studies were retrieved, applied to our cohort and corresponding sensitivity/specificity/accuracy was calculated. Optimal threshold based on our data were determined using ROC-analysis with five-fold cross validation. Moreover, a threshold with similar specificity to the 10 HU threshold in unenhanced images was calculated. Subgroup analysis of adrenal lesion differentiation depending on underlying malignancies was performed.

Results: The previously suggested thresholds were 20, 22 and 29 HU, and corresponding sensitivity/specificity/accuracy was 0.61/0.92/0.76, 0.67/0.91/0.78, and 0.82/0.59/0.71, respectively. The threshold determined from our cohort was 24.7 HU, yielding a sensitivity/specificity/accuracy of 0.76/0.81/0.79. Differentiation in disease-specific subgroups showed similar sensitivity/specificity/accuracy (Melanoma:0.78/0.84/0.79; Lung cancer:0.78/0.8/0.78; RCC:0.78/1/0.79). The VUE threshold to achieve a 0.98 specificity similar to the unenhanced 10 HU cutoff was 17.3 HU, yielding a sensitivity of 0.49.

Conclusion: Previous VUE attenuation thresholds showed a varying accuracy for differentiation between adenomas and metastases. A cross-validated VUE threshold of 24.7 HU yielded a mean accuracy of 0.79, whereas a threshold of 17.3 HU was best for achieving comparable specificity as reported for the 10 HU threshold in unenhanced images.

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来源期刊
Abdominal Radiology
Abdominal Radiology Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
5.20
自引率
8.30%
发文量
334
期刊介绍: Abdominal Radiology seeks to meet the professional needs of the abdominal radiologist by publishing clinically pertinent original, review and practice related articles on the gastrointestinal and genitourinary tracts and abdominal interventional and radiologic procedures. Case reports are generally not accepted unless they are the first report of a new disease or condition, or part of a special solicited section. Reasons to Publish Your Article in Abdominal Radiology: · Official journal of the Society of Abdominal Radiology (SAR) · Published in Cooperation with: European Society of Gastrointestinal and Abdominal Radiology (ESGAR) European Society of Urogenital Radiology (ESUR) Asian Society of Abdominal Radiology (ASAR) · Efficient handling and Expeditious review · Author feedback is provided in a mentoring style · Global readership · Readers can earn CME credits
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