Department of Oncology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
School of Computer, University of South China, Hengyang, China.
Histol Histopathol. 2024 Oct;39(10):1303-1316. doi: 10.14670/HH-18-715. Epub 2024 Jan 23.
Multispectral imaging (MSI) has been utilized to predict the prognosis of colorectal cancer (CRC) patients, however, our understanding of the prognostic value of nuclear morphological parameters of bright-field MSI in CRC is still limited. This study was designed to compare the efficiency of MSI and standard red-green-blue (RGB) images in predicting the prognosis of CRC.
We compared the efficiency of MS and conventional RGB images on the quantitative assessment of hematoxylin-eosin (HE) stained histopathology images. A pipeline was developed using a pixel-wise support vector machine (SVM) classifier for gland-stroma segmentation, and a marker-controlled watershed algorithm was used for nuclei segmentation. The correlation between extracted morphological parameters and the five-year disease-free survival (5-DFS) was analyzed.
Forty-seven nuclear morphological parameters were extracted in total. Based on Kaplan-Meier analysis, eight features derived from MS images and seven featured derived from RGB images were significantly associated with 5-DFS, respectively. Compared with RGB images, MSI showed higher accuracy, precision, and Dice index in nuclei segmentation. Multivariate analysis indicated that both integrated parameters 1 (factors negatively correlated with CRC prognosis including nuclear number, circularity, eccentricity, major axis length) and 2 (factors positively correlated with CRC prognosis including nuclear average area, area perimeter, total area/total perimeter ratio, average area/perimeter ratio) in MS images were independent prognostic factors of 5-DFS, in contrast with only integrated parameter 1 (<0.001) in RGB images. More importantly, the quantification of HE-stained MS images displayed higher accuracy in predicting 5-DFS compared with RGB images (76.9% vs 70.9%).
Quantitative evaluation of HE-stained MS images could yield more information and better predictive performance for CRC prognosis than conventional RGB images, thereby contributing to precision oncology.
多光谱成像（MSI）已被用于预测结直肠癌（CRC）患者的预后，但我们对 MSI 中亮场核形态参数对 CRC 预后的预测价值的理解仍然有限。本研究旨在比较 MSI 和标准红绿蓝（RGB）图像在预测 CRC 预后中的效率。
我们比较了 MSI 和传统 RGB 图像在苏木精-伊红（HE）染色组织病理学图像定量评估方面的效率。使用基于像素的支持向量机（SVM）分类器开发了一个用于腺体-基质分割的流水线，并使用标记控制分水岭算法进行核分割。分析提取的形态参数与五年无病生存（5-DFS）之间的相关性。
总共提取了 47 个核形态参数。基于 Kaplan-Meier 分析，MS 图像衍生的 8 个特征和 RGB 图像衍生的 7 个特征分别与 5-DFS 显著相关。与 RGB 图像相比，MSI 在核分割方面具有更高的准确性、精度和 Dice 指数。多变量分析表明，MSI 中的综合参数 1（与 CRC 预后负相关的因素，包括核数、圆形度、偏心率、长轴长度）和 2（与 CRC 预后正相关的因素，包括核平均面积、面积周长、总面积/总周长比、平均面积/周长比）均为 5-DFS 的独立预后因素，而 RGB 图像中仅为综合参数 1（<0.001）。更重要的是，与传统的 RGB 图像相比，HE 染色 MS 图像的定量分析在预测 5-DFS 方面具有更高的准确性（76.9%比 70.9%）。
与传统的 RGB 图像相比，HE 染色 MS 图像的定量评估可为 CRC 预后提供更多信息和更好的预测性能，从而有助于肿瘤精准治疗。
