The Prognostic Value of Body Composition Analysis on Non-Enhanced CT for Risk Stratification in Gastrointestinal Stromal Tumors: A Retrospective Study.

IF 2.5 4区 医学 Q3 ONCOLOGY
Cancer Control Pub Date : 2025-01-01 Epub Date: 2025-05-11 DOI:10.1177/10732748251342068
Wei Chen, Long-Yu Duan, Xiao-Juan Peng, Kun-Ming Yi, Lian-Qin Kuang
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引用次数: 0

Abstract

IntroductionContrast-enhanced computed tomography (CT) is the primary imaging modality for accurate risk stratification in gastrointestinal stromal tumors (GISTs). However, contrast-enhanced CT may not always be accessible or suitable for all patients undergoing risk assessment of GISTs. Therefore, this study explored the use of non-enhanced CT imaging for assessing body composition in patients with GISTs to preoperatively predict risk stratification.MethodsWe retrospectively analyzed 233 patients with GISTs who met the inclusion criteria. Pretreatment complete abdominal CT images from these patients were processed and analyzed using the Siemens Syngo imaging system. The data were subsequently organized and analyzed using the SPSS software (version 26.0).ResultsThrough two independent samples t-tests, Mann-Whitney U tests, and chi-square tests (including corrected chi-square tests and Fisher's exact tests), the intermediate-high risk group exhibited a lower visceral fat index (VFI) and higher tumor volumes and proportions of necrosis (P < .05), compared to the low-risk group (P < .05). No statistically significant differences were observed in the other indicators. Our research demonstrates that tumor volume is positively correlated with the National Institutes of Health (NIH) classification and exhibits the highest specificity among the four models (specificity = 0.735). However, its sensitivity is lower than that of the combined model (sensitivity = 0.803) and the VFI model (sensitivity = 0.972).ConclusionBased on the vascular abundance index, tumor volume, and necrosis status observed in the CT plain scan images of patients with GIST, a comprehensive predictive model was developed. This model can accurately predict the NIH grade of stromal tumors, thereby providing a robust basis for formulating effective treatment strategies and improving the prognosis of patients with GISTs who cannot undergo contrast-enhanced CT.

非增强CT体成分分析对胃肠道间质瘤危险分层的预后价值:一项回顾性研究。
对比增强计算机断层扫描(CT)是胃肠道间质瘤(gist)准确风险分层的主要成像方式。然而,并非所有接受gist风险评估的患者都能获得或适合使用对比增强CT。因此,本研究探讨了使用非增强CT成像评估gist患者的身体成分,以术前预测风险分层。方法对233例符合纳入标准的gist患者进行回顾性分析。使用西门子Syngo成像系统对这些患者的完整腹部CT图像进行处理和分析。随后使用SPSS软件(26.0版)对数据进行整理和分析。结果通过两个独立样本t检验、Mann-Whitney U检验和卡方检验(包括校正卡方检验和Fisher精确检验),与低危组相比,中高危组内脏脂肪指数(VFI)较低,肿瘤体积和坏死比例较高(P < 0.05)。其他指标差异无统计学意义。我们的研究表明,肿瘤体积与美国国立卫生研究院(NIH)分类呈正相关,并且在四种模型中具有最高的特异性(特异性= 0.735)。但其灵敏度低于组合模型(灵敏度= 0.803)和VFI模型(灵敏度= 0.972)。结论基于GIST患者CT平扫血管丰度指数、肿瘤体积、坏死情况,建立了综合预测模型。该模型可准确预测间质瘤的NIH分级,为制定有效的治疗策略,改善不能行增强CT的间质瘤患者的预后提供有力依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cancer Control
Cancer Control ONCOLOGY-
CiteScore
3.80
自引率
0.00%
发文量
148
审稿时长
>12 weeks
期刊介绍: Cancer Control is a JCR-ranked, peer-reviewed open access journal whose mission is to advance the prevention, detection, diagnosis, treatment, and palliative care of cancer by enabling researchers, doctors, policymakers, and other healthcare professionals to freely share research along the cancer control continuum. Our vision is a world where gold-standard cancer care is the norm, not the exception.
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