基于 F-FDG PET/CT 影像组学预测乳腺癌腋窝淋巴结转移负荷

BACKGROUND: The axillary lymph-node metastatic burden is closely associated with treatment decisions and prognosis in breast cancer patients. This study aimed to explore the value of F-fluorodeoxyglucose (F-FDG) positron emission tomography (PET)/computed tomography (CT)-based radiomics in combination with ultrasound and clinical pathological features for predicting axillary lymph-node metastatic burden in breast cancer. METHODS: A retrospective analysis was conducted and involved 124 patients with pathologically confirmed early-stage breast cancer who had undergone F-FDG PET/CT examination. The ultrasound, PET/CT, and clinical pathological features of all patients were analysed, and radiomic features from PET images were extracted to establish a multi-parameter predictive model. RESULTS: The ultrasound lymph-node positivity rate and PET lymph-node positivity rate in the high nodal burden group were significantly higher than those in the low nodal burden group (χ = 19.867, p < 0.001; χ = 33.025, p < 0.001). There was a statistically significant difference in the PET-based radiomics score (RS) for predicting axillary lymph-node burden between the high and low lymph-node burden groups. (-1.04 ± 0.41 vs. -1.47 ± 0.41, t = -4.775, p < 0.001). The ultrasound lymph-node positivity (US_LNM) (odds ratio [OR] = 3.264, 95% confidence interval [CI] = 1.022-10.423), PET lymph-node positivity (PET_LNM) (OR = 14.242, 95% CI = 2.960-68.524), and RS (OR = 5.244, 95% CI = 3.16-20.896) are all independent factors associated with high lymph-node burden (p < 0.05). The area under the curve (AUC) of the multi-parameter (MultiP) model was 0.895, which was superior to those of US_LNM, PET_LNM, and RS models (AUC = 0.703, 0.814, 0.773, respectively), with statistically significant differences (Z = 2.888, 3.208, 3.804, respectively; p = 0.004, 0.002, < 0.001, respectively). Decision curve analysis indicated that the MultiP model provided a higher net benefit for all patients. CONCLUSION: A MultiP model based on PET-based radiomics was able to effectively predict axillary lymph-node metastatic burden in breast cancer. TRIAL REGISTRATION: This study was registered with ClinicalTrials.gov (registration number: NCT05826197) on May 7, 2023.

背景：腋窝淋巴结转移负荷与乳腺癌患者的治疗决策和预后密切相关。本研究旨在探讨 F-氟脱氧葡萄糖（F-FDG）正电子发射断层扫描（PET）/计算机断层扫描（CT）-基于放射组学结合超声和临床病理特征预测乳腺癌腋窝淋巴结转移负荷的价值。

方法：回顾性分析了 124 例经病理证实的早期乳腺癌患者，这些患者均接受了 F-FDG PET/CT 检查。分析了所有患者的超声、PET/CT 和临床病理特征，并提取了 PET 图像的放射组学特征，以建立多参数预测模型。

结果：高淋巴结负荷组的超声淋巴结阳性率和 PET 淋巴结阳性率明显高于低淋巴结负荷组（χ=19.867，p<0.001；χ=33.025，p<0.001）。高和低淋巴结负荷组之间基于 PET 的放射组学评分（RS）预测腋窝淋巴结负担有统计学显著差异。（-1.04±0.41 与-1.47±0.41，t=-4.775，p<0.001）。超声淋巴结阳性（US_LNM）（比值比[OR]=3.264，95%置信区间[CI]=1.022-10.423）、PET 淋巴结阳性（PET_LNM）（OR=14.242，95%CI=2.960-68.524）和 RS（OR=5.244，95%CI=3.16-20.896）均为与高淋巴结负荷相关的独立因素（p<0.05）。多参数（MultiP）模型的曲线下面积（AUC）为 0.895，优于 US_LNM、PET_LNM 和 RS 模型（AUC=0.703、0.814、0.773，分别），差异有统计学意义（Z=2.888、3.208、3.804，分别；p=0.004、0.002、<0.001，分别）。决策曲线分析表明，MultiP 模型为所有患者提供了更高的净收益。

结论：基于 PET 放射组学的 MultiP 模型能够有效预测乳腺癌腋窝淋巴结转移负荷。

试验注册：本研究于 2023 年 5 月 7 日在 ClinicalTrials.gov 注册（注册号：NCT05826197）。