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Differentiation among prostate cancer patients with Gleason score of 7 using histopathology whole-slide image and genomic data

机译：利用组织病理学全幻灯片图像和基因组数据区分Gleason评分为7的前列腺癌患者

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Prostate cancer is the most common non-skin related cancer affecting 1 in 7 men in the United States. Treatment, of patients with prostate cancer still remains a difficult decision-making process that requires physicians to balance clinical benefits, life expectancy, comorbidities, and treatment-related side effects. Gleason score (a sum of the primary and secondary Gleason patterns) solely based on morphological prostate glandular architecture has shown as one of the best predictors of prostate cancer outcome. Significant progress has been made on molecular subtyping prostate cancer delineated through the increasing use of gene sequencing. Prostate cancer patients with Gleason score of 7 show heterogeneity in recurrence and survival outcomes. Therefore, we propose to assess the correlation between histopathology images and genomic data with disease recurrence in prostate tumors with a Gleason 7 score to identify prognostic markers. In the study, we identify image biomarkers within tissue WSIs by modeling the spatial relationship from automatically created patches as a sequence within WSI by adopting a recurrence network model, namely long short-term memory (LSTM). Our preliminary results demonstrate that integrating image biomarkers from CNN with LSTM and genomic pathway scores, is more strongly correlated with patients recurrence of disease compared to standard clinical markers and engineered image texture features. The study further demonstrates that prostate cancer patients with Gleason score of 4+3 have a higher risk of disease progression and recurrence compared to prostate cancer patients with Gleason score of 3+4.
机译：前列腺癌是最常见的非皮肤相关癌症，影响美国7人中的1位。治疗，前列腺癌的患者仍然是一个艰难的决策过程，需要医生来平衡临床效益，预期寿命，合并症和治疗相关的副作用。 Glason评分（主要和次要格子模式的总和）仅基于形态前列腺腺体建筑，已作为前列腺癌结果的最佳预测因子之一。通过越来越多的基因测序使用的分子亚型前列腺癌已经取得了重大进展。前列腺癌患者Glason评分7显示出复发和存活结果中的异质性。因此，我们建议评估组织病理学图像和基因组数据与疾病复发与前列腺肿瘤中的基因组数据与Gleason 7分数鉴定预后标志物。在该研究中，通过采用复制网络模型，即长的短期存储器（LSTM）来识别从自动创建的补丁作为WSI内的序列来识别组织WSIS内的图像生物标志物。我们的初步结果表明，与标准临床标记和工程图像纹理特征相比，与LSTM和基因组途径分数与CNN中的图像生物标志物与CNN相比更强烈地相关。该研究进一步证明，与前列腺癌患者的Glason评分为3 + 4的前列腺癌，前列腺癌患者患有Glose癌症的癌症患者，患有4 + 3的疾病进展和复发风险较高。

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