PET/CT 成像中 Ki 和 SUV 图像在病灶检测方面的优势比较。

IF 3.1 3区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

EJNMMI Research Pub Date : 2024-10-16 DOI:10.1186/s13550-024-01162-x

Danjie Cai, Yibo He, Haojun Yu, Yiqiu Zhang, Hongcheng Shi

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引用次数: 0

摘要

背景：示踪剂净流入率（Ki）成像在 PET/CT 中的临床应用仍然有限，原因是缺乏证据证明 Ki 图像在病变检测中的优越性，以及何时使用 Ki 图像的指南。本研究旨在比较 Ki 和标准化摄取值 (SUV) 图像在 PET/CT 成像中病灶检测的优势。通过分析两种技术在识别肿瘤病灶方面的表现，该研究旨在为 Ki 图像的临床应用提供指导：这项回顾性研究包括 134 名患者，244 个病理确诊病灶（200 个恶性，44 个良性）。组织病理学确诊的患者接受了基于体重的 18F-FDG 注射，并进行了 60 分钟的全身 PET/CT 动态成像。利用扫描最后 10 分钟收集的数据重建 SUV 图像。Ki图像采用Patlak方法，使用第12-60分钟的数据生成。记录了背景 SUVmax、SUVmean、SUVSD、Kimax、Kimean 和 KiSD 值。计算 SUV（SUVSNR）和 Ki（KiSNR）图像的信噪比。评估了 SUV 和 Ki 图像的病灶检测率和灵敏度。SUV和Ki图像的病灶检出率分别为97.7%（214/219）和99.5%（218/219）（p = .22）。SUV 图像上的 5 个假阴性病灶在 Ki 图像上呈真阳性（3 个肝恶性肿瘤和 2 个转移淋巴结）。SUV和Ki图像的曲线下面积[0.68（95%置信区间，0.61-0.73）vs.0.69（95%置信区间，0.62-0.74）]相似（所有P均≥.10）：结论：与 SUV 图像相比，Ki 图像在病灶检测方面具有优势，尤其是在肝脏等高背景器官中。结论：Ki 图像与 SUV 图像相比在病变检测方面具有优势，尤其是在肝脏等背景较高的器官中，Ki 图像提供的增强对比度可提高此类病例的临床检测率。

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Comparative benefits of Ki and SUV images in lesion detection during PET/CT imaging.

Background: Clinical application of the tracer net influx rate (Ki) imaging in PET/CT remains limited, due to a lack of evidence demonstrating the superiority of Ki images in lesion detection, and guidelines on when to utilize Ki images. This study aims to compare the benefits of Ki and standardized uptake value (SUV) images in lesion detection during PET/CT imaging. By analyzing the performance of both techniques in identifying tumor lesions, the study seeks to provide guidance for the clinical application of Ki images.

Results: This retrospective study included 134 patients with 244 pathologically confirmed lesions (200 malignant and 44 benign). Patients with a histopathological diagnosis received a weight-based ¹⁸F-FDG injection and underwent 60-min total-body PET/CT dynamic imaging. SUV images were reconstructed using data collected from the last 10 min of the scans. Ki images were generated using the Patlak methods with data from minutes 12-60. The background SUV_max, SUV_mean, SUV_SD, Ki_max, Ki_mean, and Ki_SD values were recorded. The signal-to-noise ratios of the SUV (SUV_SNR) and Ki (Ki_SNR) images were calculated. The lesion detection rate and sensitivity of the SUV and Ki images were evaluated. The lesion-detection rates were 97.7% (214/219) and 99.5% (218/219) for the SUV and Ki images, respectively (p = .22). Five false-negative lesions on the SUV images were true-positive on the Ki images (3 hepatic malignancies and 2 metastatic lymph nodes). The sensitivity (94.0% vs. 96.0%, p = .22), specificity (41.9% vs. 41.9%, p > .99), accuracy (84.4% vs. 86.1%, p = .61), positive predictive value (87.9% vs. 88.1%, p = .94), negative predictive value (60.0% vs. 69.2%, p = .47), and the area under the curve [0.68 (95% confidence interval, 0.61-0.73) vs. 0.69 (95% confidence interval, 0.62-0.74)] were similar in the SUV and Ki images (all p ≥ .10).

Conclusion: Ki images exhibit benefits in lesion detection compared to SUV images, particularly in organs with high background such as liver. The enhanced contrast provided by Ki imaging is recommended to clinically improve detection rates in such cases.

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来源期刊

EJNMMI Research RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING&nb-

CiteScore

5.90

自引率

3.10%

发文量

审稿时长

13 weeks

期刊介绍： EJNMMI Research publishes new basic, translational and clinical research in the field of nuclear medicine and molecular imaging. Regular features include original research articles, rapid communication of preliminary data on innovative research, interesting case reports, editorials, and letters to the editor. Educational articles on basic sciences, fundamental aspects and controversy related to pre-clinical and clinical research or ethical aspects of research are also welcome. Timely reviews provide updates on current applications, issues in imaging research and translational aspects of nuclear medicine and molecular imaging technologies. The main emphasis is placed on the development of targeted imaging with radiopharmaceuticals within the broader context of molecular probes to enhance understanding and characterisation of the complex biological processes underlying disease and to develop, test and guide new treatment modalities, including radionuclide therapy.