Pattern recognition in medical imaging

医学成像中的模式识别

• 批准号: 7969909
• 负责人: Ilya Goldberg
• 金额: $ 35.95万
• 依托单位: NATIONAL INSTITUTE ON AGING
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7969909
• 关键词: Affect; Aging; Animal Model; Baltimore; Biological; Biological Markers; Biopsy; Caenorhabditis elegans; Classification; Collection; Computers; Degenerative polyarthritis; Development; Diagnosis; Diet; Disease; Disease Progression; Evolution; Eye; Future; Goals; Homeostasis; Human; Image; Image Analysis; Individual; Intervention; Knee; Knowledge; Lead; Life; Link; Longitudinal Studies; MRI Scans; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of prostate; Measures; Medical; Medical Imaging; Morphology; Neoplasm Metastasis; Organism; Pattern; Pattern Recognition; Pharmaceutical Preparations; Pharyngeal structure; Physiological; Physiological Processes; Physiology; Population; Process; Property; Publishing; Resolution; Resveratrol; Roentgen Rays; Sampling; Staging; Staining method; Stains; Study Section; Surveys; System; Systems Analysis; Time; Tissue Microarray; Tissues; Training; Work; age related; base; cancer type; clinical Diagnosis; clinically relevant; functional decline; human disease; image processing; melanoma; muscle degeneration; outcome forecast; prevent; radiologist; sarcopenia; success; tool; tumor progression

Recent work in pattern recognition has demonstrated that computers can equal or even surpass image classification and pattern analysis by human experts. Modern imaging systems far exceed the human eye in spatial and spectral resolution as well as dynamic range, thus potentially allowing machine-based image pattern analysis systems to perform such tasks. The pattern analysis system we have developed, characterized and published is called WND-CHARM. A key property of WND-CHARM is that it can provide quantitative measures of image similarity. Quantitative comparisons between individual images or groups of images allow the establishment of a time-course for the progression of a physiological process represented by images. An independent verification that the continuous evolution of morphological patterns in a process are detected by the computer is its ability to place these images in order without a priori knowledge. Subsequently, the degree of change from one timepoint to another can be used to determine if the physiological process is smooth and continuous, or progresses through discrete stages. Discontinuous processes imply the presence of biological control at the transitions, and may point to key stages for medical interventions. Our published work has shown that age-related muscle degeneration (sarcopenia) in the C. elegans pharynx occurs in three discrete stages. This was the first characterization of discrete post-developmental morphological states in any organism. The observation that muscle degeneration occurs in stages implies that it may be a regulated process, and may be subject to interventions to prevent or delay these transitions. Our current work will investigate if these stages can be consistently observed in mammalian tissues, and whether interventions such as diet and the drug resveratrol affects the timing or magnitude of these morphological changes. We have also published our work on investigating the progression of osteoarthritis (OA) in the human population comprising the Baltimore Longitudinal Study of Aging (BLSA). We were able to show that WND-CHARM is able to diagnose the existence of OA in knee X-Rays with accuracies approaching that of a panel of highly trained radiologists. More recently, we have published work that WND-CHARM can predict the future onset of radiologically detectable osteoarthritis in X-Rays that were scored as radiologically clear. We were able to show that the development of moderate OA two decades in the future can be predicted with > 70% accuracy from an X-Ray scored as free of OA by a panel of three radiologists. Our current work in OA continues with the analysis of 5000 MRI scans from the Osteoarthritis Initiative. Our work with processing images of H&E-stained sections of cancer biopsies has shown that consistency of sectioning and staining is a key factor in effective image analysis of medical samples. Our initial success diagnosing and sub-classifying melanoma metastases has led us to expand this analysis to a survey of several types of cancers available as commercial tissue microarrays. Our success with this pilot survey will be followed by a more detailed study of the association between morphology/physiology and diagnosis/prognosis in prostate cancer, where a link between morphology and prognosis is already established.

最新的模式识别工作表明，计算机可以平等甚至超过人类专家的图像分类和模式分析。 现代成像系统在空间和光谱分辨率以及动态范围内远远超过了人类的眼睛，因此有可能允许基于机器的图像模式分析系统执行此类任务。 我们开发，表征和发布的模式分析系统称为WND-Charm。 WND-Charm的关键特性是它可以提供图像相似性的定量度量。 单个图像或图像组之间的定量比较允许建立时间课程，以进行图像所示的生理过程的进展。 一个独立的验证，即计算机检测到过程中形态模式的连续演变是其在没有先验知识的情况下按顺序放置这些图像的能力。 随后，可以使用从一个时间点到另一个时间点的变化程度来确定生理过程是平稳且连续的，还是通过离散阶段进行。 不连续的过程意味着在过渡时存在生物控制，并且可能指出了医疗干预措施的关键阶段。 我们发表的工作表明，秀丽隐杆线虫咽的与年龄相关的肌肉变性（Sarcopenia）在三个离散阶段发生。 这是任何生物体中离散发育后形态状态的第一个表征。 肌肉退化的观察结果可能是一个受调节的过程，并且可能受到预防或延迟这些过渡的干预措施。 我们目前的工作将调查是否可以在哺乳动物组织中始终观察到这些阶段，以及饮食和药物白藜芦醇等干预措施是否会影响这些形态学变化的时间或幅度。 我们还发表了有关研究巴尔的摩衰老纵向研究（BLSA）的人口中骨关节炎（OA）进展的工作。 我们能够证明，WND-Charm能够诊断出膝盖X射线中的OA存在，而精度接近了一组受过训练的放射科医生。 最近，我们发表了WND-CHARM可以预测X射线中可检测到的放射学检测到的骨关节炎的未来发作的工作，这在放射学上很清楚。 我们能够证明，未来中度OA的发展可以通过三位放射科医生的小组无OA得分，以> 70％的精度预测，可以预测70％的精度。 我们目前在OA中的工作继续进行了对骨关节炎倡议的5000次MRI扫描的分析。 我们在处理癌症活检的H＆E染色部分的处理图像的工作表明，切片和染色的一致性是对医疗样品有效图像分析的关键因素。 我们最初的成功诊断和亚分类的黑色素瘤转移使我们扩大了对商业组织微阵列可用的癌症的调查。 在这项试验调查中，我们的成功将在前列腺癌中对形态/生理学与诊断/预后之间的关联进行更详细的研究，在这种情况下，已经建立了形态学与预后之间的联系。