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Abstract：
BACKGROUND: Pseudomyxoma peritonei (PMP) is a rare clinical malignant syndrome, and its rarity causes a lack of pathology research. This study aims to quantitatively analyze HE-stained pathological images (PIs), and develop a new predictive model integrating digital pathological parameters with clinical information.
METHODS: Ninety-two PMP patients with complete clinic-pathological information, were included. QuPath was used for PIs quantitative feature analysis at tissue-, cell-, and nucleus-level. The correlations between overall survival (OS) and general clinicopathological characteristics, and PIs features were analyzed. A nomogram was established based on independent prognostic factors and evaluated.
RESULTS: Among the 92 PMP patients, there were 34 (37.0%) females and 58 (63.0%) males, with a median age of 57 (range: 31-76). A total of 449 HE stained images were obtained for QuPath analysis, which extracted 40 pathological parameters at three levels. Kaplan-Meier survival analysis revealed eight clinicopathological characteristics and 20 PIs features significantly associated with OS (p < 0.05). Partial least squares regression was used to screen the multicollinearity features and synthesize four new features. Multivariate survival analysis identified the following five independent prognostic factors: preoperative CA199, completeness of cytoreduction, histopathological type, component one at tissue-level, and tumor nuclei circularity variance. A nomogram was established with internal validation C-index 0.795 and calibration plots indicating improved prediction performance.
CONCLUSIONS: The quantitative analysis of HE-stained PIs could extract the new prognostic information on PMP. A nomogram established by five independent prognosticators is the first model integrating digital pathological information with clinical data for improved clinical outcome prediction.
METHODS: Ninety-two PMP patients with complete clinic-pathological information, were included. QuPath was used for PIs quantitative feature analysis at tissue-, cell-, and nucleus-level. The correlations between overall survival (OS) and general clinicopathological characteristics, and PIs features were analyzed. A nomogram was established based on independent prognostic factors and evaluated.
RESULTS: Among the 92 PMP patients, there were 34 (37.0%) females and 58 (63.0%) males, with a median age of 57 (range: 31-76). A total of 449 HE stained images were obtained for QuPath analysis, which extracted 40 pathological parameters at three levels. Kaplan-Meier survival analysis revealed eight clinicopathological characteristics and 20 PIs features significantly associated with OS (p < 0.05). Partial least squares regression was used to screen the multicollinearity features and synthesize four new features. Multivariate survival analysis identified the following five independent prognostic factors: preoperative CA199, completeness of cytoreduction, histopathological type, component one at tissue-level, and tumor nuclei circularity variance. A nomogram was established with internal validation C-index 0.795 and calibration plots indicating improved prediction performance.
CONCLUSIONS: The quantitative analysis of HE-stained PIs could extract the new prognostic information on PMP. A nomogram established by five independent prognosticators is the first model integrating digital pathological information with clinical data for improved clinical outcome prediction.
摘要：
背景：腹膜假粘液瘤（PMP）是一种罕见的临床恶性综合征，它的稀有性导致缺乏病理学研究。本研究旨在定量分析HE染色的病理图像（PIs），并开发了一种将数字病理参数与临床信息相结合的新预测模型。
方法：92例有完整临床病理资料的PMP患者，包括在内。QuPath用于组织的PI定量特征分析，cell-,和核级。总生存期（OS）与一般临床病理特征之间的相关性，并对PI特征进行了分析。根据独立的预后因素建立列线图并进行评估。
结果：在92例PMP患者中，女性34人(37.0%),男性58人(63.0%),年龄中位数为57岁（范围：31-76）。共获得449张HE染色图像进行QuPath分析。从三个层次提取了40个病理参数。Kaplan-Meier生存分析显示8个临床病理特征和20个PI特征与OS显著相关(p<0.05)。采用偏最小二乘回归对多重共线性特征进行筛选,并合成4个新特征。多变量生存分析确定了以下五个独立的预后因素：术前CA199，细胞减记术的完整性，组织病理学类型,组织水平的成分之一，和肿瘤核圆形度方差。建立了具有内部验证C指数0.795和校准图的列线图，表明预测性能得到了改善。
结论：HE染色的PIs定量分析可以提取PMP的新预后信息。由五个独立的预测者建立的列线图是第一个将数字病理信息与临床数据相结合以改善临床结果预测的模型。
方法：92例有完整临床病理资料的PMP患者，包括在内。QuPath用于组织的PI定量特征分析，cell-,和核级。总生存期（OS）与一般临床病理特征之间的相关性，并对PI特征进行了分析。根据独立的预后因素建立列线图并进行评估。
结果：在92例PMP患者中，女性34人(37.0%),男性58人(63.0%),年龄中位数为57岁（范围：31-76）。共获得449张HE染色图像进行QuPath分析。从三个层次提取了40个病理参数。Kaplan-Meier生存分析显示8个临床病理特征和20个PI特征与OS显著相关(p<0.05)。采用偏最小二乘回归对多重共线性特征进行筛选,并合成4个新特征。多变量生存分析确定了以下五个独立的预后因素：术前CA199，细胞减记术的完整性，组织病理学类型,组织水平的成分之一，和肿瘤核圆形度方差。建立了具有内部验证C指数0.795和校准图的列线图，表明预测性能得到了改善。
结论：HE染色的PIs定量分析可以提取PMP的新预后信息。由五个独立的预测者建立的列线图是第一个将数字病理信息与临床数据相结合以改善临床结果预测的模型。
