迭代 OSEM 算法和 HYPER 算法在 18F-FDG 活性低、采集时间短和病灶小的情况下进行 SUVmax 全身正电子发射计算机断层显像的性能。

IF 1.1 4区 医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Current Medical Imaging Reviews Pub Date : 2024-03-25 DOI:10.2174/0115734056274225240109112413
Keyu Zan, Yanhua Duan, Minjie Zhao, Hui Li, Xiao Cui, Leiying Chai, Zhaoping Cheng
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引用次数: 0

摘要

目的这项比较研究的主要目的是,在全身 18F- FDG PET/CT 中,在不同的采集持续时间和注射活动下,利用两种不同的算法(即 OSEM 和 HYPER Iterative)检查图像重建的质量属性:方法:使用 NEMA 模体进行初步评估,比较 OSEM 和 HYPER Iterative 算法生成的图像质量。对 BV、COV 和 CRC 等参数进行了细致的评估。随后,采用这两种重建算法对 50 名患者进行了前瞻性队列研究。研究分为不同的采集时间和剂量组。根据病变大小进一步分为三组。研究人员计算了噪音标度、SUVmax、SNR 和 TBR 等量化指标。此外,还计算了OSEM和HYPER迭代算法的差异值,即ΔSUVmax、ΔTBR、%ΔSUVmax、%ΔSD和%ΔSNR:在采集时间不变的情况下,HYPER迭代算法与OSEM相比,在模型研究中降低了BV和COV。在临床研究中,使用 HYPER Iterative 算法重建的图像与 OSEM 生成的图像相比,病变 SUVmax、TBR 和 SNR 显著增加(p < 0.001)。此外,SUVmax 的增幅主要体现在尺寸小于 10 毫米的病灶上。HYPER Iterative 的信噪比(SNR)%Δ和标度(SD)%Δ等指标的改善与采集时间和剂量的减少有关,其中 SUVmax 和 TBR 的增强程度更为明显:结论:HYPER Iterative 算法能显著提高 SUVmax 值并降低噪音水平,在病变面积小于 10 毫米以及采集时间缩短和剂量降低的条件下尤其有效。
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Performance of the Iterative OSEM and HYPER Algorithm for Total-body PET at SUVmax with a Low 18F-FDG Activity, a Short Acquisition Time and Small Lesions.

Objective: The primary objective of this comparative investigation was to examine the qualitative attributes of image reconstructions utilizing two distinct algorithms, namely OSEM and HYPER Iterative, in total-body 18F- FDG PET/CT under various acquisition durations and injection activities.

Methods: An initial assessment was executed using a NEMA phantom to compare image quality engendered by OSEM and HYPER Iterative algorithms. Parameters such as BV, COV, and CRC were meticulously evaluated. Subsequently, a prospective cohort study was conducted on 50 patients, employing both reconstruction algorithms. The study was compartmentalized into distinct acquisition time and dosage groups. Lesions were further categorized into three size-based groups. Quantifiable metrics including SD of noise, SUVmax, SNR, and TBR were computed. Additionally, the differences in values, namely ΔSUVmax, ΔTBR, %ΔSUVmax, %ΔSD, and %ΔSNR, between OSEM and HYPER Iterative algorithms were also calculated.

Results: The HYPER Iterative algorithm showed reduced BV and COV compared to OSEM in the phantom study, with constant acquisition time. In the clinical study, lesion SUVmax, TBR, and SNR were significantly elevated in images reconstructed using the HYPER Iterative algorithm in comparison to those generated by OSEM (p < 0.001). Furthermore, an amplified increase in SUVmax was predominantly discernible in lesions with dimensions less than 10 mm. Metrics such as %ΔSNR and %ΔSD in HYPER Iterative exhibited improvements correlating with reduced acquisition times and dosages, wherein a more pronounced degree of enhancement was observable in both ΔSUVmax and ΔTBR.

Conclusion: The HYPER Iterative algorithm significantly improves SUVmax and reduces noise level, with particular efficacy in lesions measuring ≤ 10 mm and under conditions of abbreviated acquisition times and lower dosages.

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来源期刊
CiteScore
2.60
自引率
0.00%
发文量
246
审稿时长
1 months
期刊介绍: Current Medical Imaging Reviews publishes frontier review articles, original research articles, drug clinical trial studies and guest edited thematic issues on all the latest advances on medical imaging dedicated to clinical research. All relevant areas are covered by the journal, including advances in the diagnosis, instrumentation and therapeutic applications related to all modern medical imaging techniques. The journal is essential reading for all clinicians and researchers involved in medical imaging and diagnosis.
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