PET/CT Radiomics Integrated with Clinical Indexes as a Tool to Predict Ki67 in Breast Cancer: a Pilot Study.

IF 1.3 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Nuclear Medicine and Molecular Imaging Pub Date : 2025-06-01 Epub Date: 2024-11-29 DOI:10.1007/s13139-024-00896-9

Dawei Li, Hui Ding, Yuting Liao, Xiao Yu, Youmin Guo, Cong Shen

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引用次数: 0

Abstract

Objective: This study aims to assess the value of radiomics features integrated with clinical characteristics for estimating Ki67 expression in patients with breast cancer (BC).

Methods: In total, 114 patients with BC performed ¹⁸F-FDG PET/CT scans. Patients were randomly assigned to a training set (n = 79, 55 cases of Ki67 + and 24 cases of Ki67-) and a validation set (n = 35, 24 cases of Ki67 + and 11 cases of Ki67-). Thirteen clinical characteristics and 704 radiomics features were extracted, and 4 clinical and 8 radiomics features were selected. Three models were developed, including the clinical model, the radiomics model, and the combined model. Model performance was evaluated using the ROC curve, and clinical utility was assessed through decision curve analysis (DCA).

Results: The N stage, tumor morphology, SUVmax, and the longest diameter significantly differed between Ki67 + and Ki67- groups (all P < 0.05). Eight radiomics features were selected for the radiomics model. The area under the curve of the combined model in the training and test group was 0.90 (95% CI: 0.82∼0.97) and 0.81 (95% CI: 0.64∼0.99), respectively. The combined model significantly outperformed both the radiomics model and the clinical model alone (P < 0.05). The DCA curve demonstrated the superior clinical utility of the combined model compared to the clinical model and radiomics model.

Conclusions: PET/CT image-based radiomics features combined with clinical features have the potential to predict Ki67 expression in BC.

Supplementary information: The online version contains supplementary material available at 10.1007/s13139-024-00896-9.

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结合临床指标的PET/CT放射组学作为预测乳腺癌Ki67的工具：一项初步研究。

目的：本研究旨在评估结合临床特征的放射组学特征在乳腺癌（BC）患者中评估Ki67表达的价值。方法：114例BC患者行18F-FDG PET/CT扫描。患者被随机分配到训练集（n = 79, 55例Ki67 +和24例Ki67-）和验证集（n = 35, 24例Ki67 +和11例Ki67-）。提取13个临床特征和704个放射组学特征，筛选出4个临床特征和8个放射组学特征。建立了临床模型、放射组学模型和联合模型。采用ROC曲线评估模型性能，采用决策曲线分析（DCA）评估临床效用。结果：Ki67 +组和Ki67-组的N分期、肿瘤形态、SUVmax、最长直径均有显著差异（P < 0.05）。结论：基于PET/CT图像的放射组学特征结合临床特征有可能预测Ki67在BC中的表达。补充信息：在线版本包含补充资料，下载地址：10.1007/s13139-024-00896-9。

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来源期刊

Nuclear Medicine and Molecular Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-

CiteScore

2.20

自引率

7.70%

发文量

期刊介绍： Nuclear Medicine and Molecular Imaging (Nucl Med Mol Imaging) is an official journal of the Korean Society of Nuclear Medicine, which bimonthly publishes papers on February, April, June, August, October, and December about nuclear medicine and related sciences such as radiochemistry, radiopharmacy, dosimetry and pharmacokinetics / pharmacodynamics of radiopharmaceuticals, nuclear and molecular imaging analysis, nuclear and molecular imaging instrumentation, radiation biology and radionuclide therapy. The journal specially welcomes works of artificial intelligence applied to nuclear medicine. The journal will also welcome original works relating to molecular imaging research such as the development of molecular imaging probes, reporter imaging assays, imaging cell trafficking, imaging endo(exo)genous gene expression, and imaging signal transduction. Nucl Med Mol Imaging publishes the following types of papers: original articles, reviews, case reports, editorials, interesting images, and letters to the editor. The Korean Society of Nuclear Medicine (KSNM) KSNM is a scientific and professional organization founded in 1961 and a member of the Korean Academy of Medical Sciences of the Korean Medical Association which was established by The Medical Services Law. The aims of KSNM are the promotion of nuclear medicine and cooperation of each member. The business of KSNM includes holding academic meetings and symposia, the publication of journals and books, planning and research of promoting science and health, and training and qualification of nuclear medicine specialists.