Latent biomarkers are quantities that strongly relate to patient's disease diagnosis and prognosis, but are difficult to measure or even not directly observable. The objective of this study was to develop, analyze and validate new priors for Bayesian inference of such biomarkers. Theoretical analysis revealed a relationship between the estimates inferred from the model and the true values of measured quantities, and the impact of the priors. This led to a new prior encoding scheme that incorporates objectively measurable domain knowledge, i.e. by performing two measurements with a reference method, which imply scale of the prior distribution. Second, priors on parameters of systematic error are non-informative, which enables biomarker estimation from a set of different quantities. Analysis showed that the volume of nucleus basalis of Meynert, which is reduced in early stages of Alzheimer's dementia and Parkinson's disease, is inter-related and could be inferred from compartmental brain volume measurements performed on routine clinical MR scans. Another experiment showed that total lesion load, associated to future disability progression in multiple sclerosis patients, could be inferred from lesion volume measurements based on multiple automated MR scan segmentations. Besides, figures of merit derived from the estimates could, without comparing against reference gold standard segmentations, identify the best performing lesion segmentation method. The proposed new priors substantially simplify the application of Bayesian inference for latent biomarkers and thus open an avenue for clinical implementation of new biomarkers, which may ultimately advance the evidence-based medicine.

中文翻译：

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潜在生物标记的贝叶斯推断的实用先验

潜在的生物标志物是与患者疾病的诊断和预后密切相关的量，但难以测量甚至无法直接观察到。这项研究的目的是开发，分析和验证贝叶斯推断此类生物标志物的新先验。理论分析表明，从模型推断出的估计值与实测值的真实值之间的关系以及先验的影响。这导致了一种新的先验编码方案，该方案结合了客观可测量的领域知识，即通过使用参考方法执行两次测量来暗示先验分布的规模。第二，关于系统误差参数的先验是非信息性的，这使得能够根据一组不同的量来估计生物标志物。分析表明，Meynert基底核的体积，它在阿尔茨海默氏痴呆症和帕金森氏病的早期阶段减少，是相互关联的，可以从常规临床MR扫描进行的隔室脑容量测量中推断出来。另一个实验表明，总的病变负荷与多发性硬化症患者未来的残障发展有关，可以从基于多个自动MR扫描分割的病变体积测量结果中推断出来。此外，从估计中得出的品质因数无需与参考金标准分割进行比较即可确定性能最佳的病变分割方法。拟议的新先验实质上简化了对潜在生物标志物的贝叶斯推论的应用，从而为新生物标志物的临床实施开辟了一条途径，这最终可能会推动循证医学的发展。