Iodine quantification of renal lesions: Preliminary results using spectral-based material extraction on photon-counting CT.

IF 1.1 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Journal of Clinical Imaging Science Pub Date : 2024-03-08 eCollection Date: 2024-01-01 DOI:10.25259/JCIS_1_2024
Adrienn Tóth, Jordan H Chamberlin, Salvador Mendez, Akos Varga-Szemes, Andrew D Hardie
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Abstract

Objectives: To assess the range of quantitative iodine values in renal cysts (RC) (with a few renal neoplasms [RNs] as a comparison) to develop an expected range of values for RC that can be used in future studies for their differentiation.

Material and methods: Consecutive patients (n = 140) with renal lesions who had undergone abdominal examination on a clinical photon-counting computed tomography (PCCT) were retrospectively included. Automated iodine quantification maps were reconstructed, and region of interest (ROI) measurements of iodine concentration (IC) (mg/cm3) were performed on whole renal lesions. In addition, for heterogeneous lesions, a secondary ROI was placed on the area most suspicious for malignancy. The discriminatory values of minimum, maximum, mean, and standard deviation for IC were compared using simple logistic regression and receiver operating characteristic curves (area under the curve [AUC]).

Results: A total of 259 renal lesions (243 RC and 16 RN) were analyzed. There were significant differences between RC and RN for all IC measures with the best-performing metrics being mean and maximum IC of the entire lesion ROI (AUC 0.912 and 0.917, respectively) but also mean and minimum IC of the most suspicious area in heterogeneous lesions (AUC 0.983 and 0.992, respectively). Most RC fell within a range of low measured iodine values although a few had higher values.

Conclusion: Automated iodine quantification maps reconstructed from clinical PCCT have a high diagnostic ability to differentiate RCs and neoplasms. The data from this pilot study can be used to help establish quantitative values for clinical differentiation of renal lesions.

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肾脏病变的碘定量:在光子计数 CT 上使用基于光谱的材料提取技术的初步结果。
研究目的评估肾囊肿(RC)的定量碘值范围(以少量肾肿瘤[RNs]作为对比),以制定RC的预期值范围,供今后的研究用于区分RC:回顾性纳入在临床光子计数计算机断层扫描(PCCT)上接受腹部检查的肾脏病变连续患者(n = 140)。重建了自动碘定量图,并对整个肾脏病变进行了碘浓度(IC)(毫克/立方厘米)的感兴趣区(ROI)测量。此外,对于异质性病变,还在最可疑的恶性病变区域设置了辅助 ROI。利用简单逻辑回归和接收者操作特征曲线(曲线下面积 [AUC])比较了 IC 的最小值、最大值、平均值和标准偏差的判别值:共分析了 259 例肾脏病变(243 例 RC 和 16 例 RN)。RC 和 RN 在所有 IC 指标上都存在明显差异,表现最好的指标是整个病变 ROI 的平均 IC 和最大 IC(AUC 分别为 0.912 和 0.917),以及异质性病变中最可疑区域的平均 IC 和最小 IC(AUC 分别为 0.983 和 0.992)。尽管少数病灶的碘值较高,但大多数病灶的碘值都处于较低的测量值范围内:结论:根据临床 PCCT 重建的自动碘定量图在区分 RC 和肿瘤方面具有很高的诊断能力。这项试点研究的数据可用于帮助建立临床区分肾脏病变的定量值。
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来源期刊
Journal of Clinical Imaging Science
Journal of Clinical Imaging Science RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
2.00
自引率
0.00%
发文量
65
期刊介绍: The Journal of Clinical Imaging Science (JCIS) is an open access peer-reviewed journal committed to publishing high-quality articles in the field of Imaging Science. The journal aims to present Imaging Science and relevant clinical information in an understandable and useful format. The journal is owned and published by the Scientific Scholar. Audience Our audience includes Radiologists, Researchers, Clinicians, medical professionals and students. Review process JCIS has a highly rigorous peer-review process that makes sure that manuscripts are scientifically accurate, relevant, novel and important. Authors disclose all conflicts, affiliations and financial associations such that the published content is not biased.
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