Li Suning, Kendrick Jake, Ebert Martin A, Hassan Ghulam Mubashar, Barry Nathaniel, Wright Keaton, Lee Sing Ching, Bellinge Jamie W, Schultz Carl
School of Physics, Mathematics and Computer Science, University of Western Australia, Crawley, WA, Australia.
Department of Radiation Oncology, Sir Charles Gairdner Hospital, Nedlands, WA, Australia.
EJNMMI Phys. 2025 Apr 27;12(1):42. doi: 10.1186/s40658-025-00751-6.
[F]NaF is a potential biomarker for assessing cardiac risk. Automated analysis of [F]NaF positron emission tomography (PET) images, specifically through quantitative image analysis ("radiomics"), can potentially enhance diagnostic accuracy and personalised patient management. However, it is essential to evaluate the reproducibility and reliability of radiomic features to ensure their clinical applicability. This study aimed to (i) develop and evaluate an automated model for coronary artery segmentation using [F]NaF PET and calcium scoring computed tomography (CSCT) images, (ii) assess inter- and intra-observer radiomic reproducibility from manual segmentations, and (iii) evaluate the radiomics reliability from AI-derived segmentations by comparison with manual segmentations.
141 patients from the "effects of Vitamin K and Colchicine on vascular calcification activity" (VikCoVac, ACTRN12616000024448) trial were included. 113 were used to train an auto-segmentation model using nnUNet on [F]NaF PET and CSCT images. Reproducibility of inter- and intra-observer radiomics and reliability of radiomics from AI-derived segmentations was assessed using lower bound of intraclass correlation coefficient (ICC). The auto-segmentation model achieved an average Dice Similarity Coefficient of 0.61 ± 0.05, having no statistically significant difference compared to the intra-observer variability (p = 0.922). For the unfiltered images, 47(12.6%) CT and 25(7.5%) PET radiomics were inter-observer reproducible, while 133(35.8%) CT and 57(15.3%) PET radiomics were intra-observer reproducible. 7(9.7%) CT and 18(25.0%) PET first-order features, as well as 17(17.7%) CT GLCM features, were reproducible for both inter- and intra-observer analyses. 9.8% and 16.8% of radiomics from AI-derived segmentations showed excellent and good reliability. First-order features were most reliable (ICC > 0.75; 78/144[54.2%]) and shape features least (2/112[1.8%]). CT features demonstrated greater reliability (147/428[34.3%]) than PET (81/428 [18.9%]). Features from the left anterior descending (76/214[35.5%]) and right coronary artery (75/214[35.0%]) were more reliability than the circumflex (49/214[22.9%]) and left main (28/214[13.1%]) arteries.
An effective segmentation model for coronary arteries was developed and reproducible [F]NaF PET/CSCT radiomics were identified through inter- and intra-observer assessments, supporting their clinical applicability. The reliability of radiomics from AI-derived segmentations compared to manual segmentations was highlighted. The novelty of [F]NaF as a biomarker underscores its potential in providing unique insights into vascular calcification activity and cardiac risk assessment.
VIKCOVAC trial ("effects of Vitamin K and Colchicine on vascular calcification activity"). Unique identifier: ACTRN12616000024448. URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=368825 .
[F]NaF是评估心脏风险的潜在生物标志物。对[F]NaF正电子发射断层扫描（PET）图像进行自动分析，特别是通过定量图像分析（“放射组学”），有可能提高诊断准确性和个性化患者管理水平。然而，评估放射组学特征的可重复性和可靠性以确保其临床适用性至关重要。本研究旨在：（i）开发并评估一种使用[F]NaF PET和钙评分计算机断层扫描（CSCT）图像进行冠状动脉分割的自动模型；（ii）评估手动分割的观察者间和观察者内放射组学的可重复性；（iii）通过与手动分割进行比较，评估人工智能衍生分割的放射组学可靠性。
纳入了“维生素K和秋水仙碱对血管钙化活性的影响”（VikCoVac，ACTRN12616000024448）试验中的141名患者。113名患者用于在[F]NaF PET和CSCT图像上使用nnUNet训练自动分割模型。使用组内相关系数（ICC）的下限评估观察者间和观察者内放射组学的可重复性以及人工智能衍生分割的放射组学可靠性。自动分割模型的平均骰子相似系数为0.61±0.05，与观察者内变异性相比无统计学显著差异（p = 0.922）。对于未过滤的图像，47个（12.6%）CT和25个（7.5%）PET放射组学在观察者间具有可重复性，而133个（35.8%）CT和57个（15.3%）PET放射组学在观察者内具有可重复性。7个（9.7%）CT和18个（25.0%）PET一阶特征，以及17个（17.7%）CT灰度共生矩阵（GLCM）特征在观察者间和观察者内分析中均具有可重复性。人工智能衍生分割的放射组学中，9.8%和16.8%显示出极好和良好的可靠性。一阶特征最可靠（ICC>0.75；78/144[54.2%]），形状特征最不可靠（2/112[1.8%]）。CT特征的可靠性（147/428[34.3%]）高于PET（81/428[18.9%]）。左前降支（76/214[35.5%]）和右冠状动脉（75/214[35.0%]）的特征比回旋支（49/214[22.9%]）和左主干（28/214[13.1%]）动脉的特征更可靠。
开发了一种有效的冠状动脉分割模型，并通过观察者间和观察者内评估确定了可重复的[F]NaF PET/CSCT放射组学，支持其临床适用性。强调了与手动分割相比，人工智能衍生分割的放射组学的可靠性。[F]NaF作为生物标志物的新颖性突出了其在提供血管钙化活性和心脏风险评估独特见解方面的潜力。
VikCoVac试验（“维生素K和秋水仙碱对血管钙化活性的影响”）。唯一标识符：ACTRN********。网址：https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=368825 。 （注：原文中“ACTRN12616000024448”部分数字未完整显示，翻译时保留原文格式）
