Department of Radiology, the Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), No. 127 Dongming Road, Zhengzhou, 450008, Henan, China.
Department of Gastrointestinal Oncology, the Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou, Henan, China.
Eur Radiol. 2023 Jul;33(7):5172-5183. doi: 10.1007/s00330-023-09464-9. Epub 2023 Feb 24.
This work focused on developing and validating the spectral CT-based nomogram to preoperatively predict perineural invasion (PNI) for locally advanced gastric cancer (LAGC).
This work prospectively included 196 surgically resected LAGC patients (139 males, 57 females, 59.55 ± 11.97 years) undergoing triple enhanced spectral CT scans. Patients were labeled as perineural invasion (PNI) positive and negative according to pathologic reports, then further split into primary (n = 130) and validation cohort (n = 66). We extracted clinicopathological information, follow-up data, iodine concentration (IC), and normalized IC values against to aorta (nICs) at arterial/venous/delayed phases (AP/VP/DP). Clinicopathological features and IC values between PNI positive and negative groups were compared. Multivariable logistic regression was performed to screen independent risk factors of PNI. Then, a nomogram was established, and its capability was determined by ROC curves. Its clinical use was evaluated by decision curve analysis. The correlations of PNI and the nomogram with patients' survival were explored by log-rank survival analysis.
Borrmann classification, tumor thickness, and nICDP were independent predictors of PNI and used to build the nomogram. The nomogram yielded higher AUCs of 0.853 (0.744-0.928) and 0.782 (0.701-0.850) in primary and validation cohorts than any other parameters (p < 0.05). Both PNI and the nomogram were related to post-surgical treatment planning. Only PNI was associated with disease-free survival in the primary cohort (p < 0.05).
This work prospectively established a spectral CT-based nomogram, which can effectively predict PNI preoperatively and potentially guide post-surgical treatment strategy in LAGC.
• The present prospective study established a spectral CT-based nomogram for preoperative prediction of perineural invasion in LAGC. • The proposed nomogram, including morphological features and the quantitative iodine concentration values from spectral CT, had the potential to predict PNI for LAGC before surgery, along with guide post-surgical treatment planning. • Normalized iodine concentration at the delayed phase was the most valuable quantitative parameter, suggesting the importance of delayed enhancement in gastric CT.
本研究旨在开发并验证基于能谱 CT 的列线图,以术前预测局部进展期胃癌(LAGC)的神经周围侵犯(PNI)。
本前瞻性研究纳入了 196 例接受三期增强能谱 CT 扫描的手术切除的 LAGC 患者(男性 139 例,女性 57 例,年龄 59.55±11.97 岁)。根据病理报告,患者被标记为 PNI 阳性和阴性,然后进一步分为原发性队列(n=130)和验证队列(n=66)。我们提取了临床病理特征、随访数据、碘浓度(IC)以及动脉/静脉/延迟期(AP/VP/DP)的主动脉标准化碘浓度值(nICs)。比较了 PNI 阳性和阴性组之间的临床病理特征和 IC 值。多变量逻辑回归筛选 PNI 的独立危险因素。然后,建立列线图,并通过 ROC 曲线确定其效能。通过决策曲线分析评估其临床应用。通过对数秩生存分析探讨 PNI 和列线图与患者生存的相关性。
Borrman 分类、肿瘤厚度和 nICDP 是 PNI 的独立预测因素,用于构建列线图。列线图在原发性和验证队列中的 AUC 分别为 0.853(0.744-0.928)和 0.782(0.701-0.850),明显高于其他参数(p<0.05)。PNI 和列线图均与术后治疗计划有关。仅在原发性队列中,PNI 与无病生存相关(p<0.05)。
本前瞻性研究建立了一种基于能谱 CT 的列线图,可有效预测 LAGC 的 PNI,可能有助于指导 LAGC 的术后治疗策略。
本前瞻性研究建立了一种基于能谱 CT 的列线图,用于预测 LAGC 的 PNI。
该列线图包含形态学特征和能谱 CT 的定量碘浓度值,有可能在术前预测 LAGC 的 PNI,并指导术后治疗计划。
延迟期的标准化碘浓度是最有价值的定量参数,提示胃 CT 延迟增强的重要性。