MRI Imaging and Biomarkers for Early Detection of Aggressive Prostate Cancer

用于早期检测侵袭性前列腺癌的 MRI 成像和生物标志物

• 批准号: 10481836
• 负责人: Alan Pollack
• 金额: $ 57.02万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-16 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10481836
• 关键词: 3-Dimensional; Algorithms; Attention; Biological Markers; Biopsy; Blood; Body Fluids; Cells; Cessation of life; Characteristics; Classification; Clinical; Clinical Trials; Collaborations; Complement; Data; Detection; Diagnosis; Diagnostic; Early Detection Research Network; Early Diagnosis; Early identification; Evolution; Funding; Gene Expression; Genomics; Gland; Gleason Grade for Prostate Cancer; Goals; Habitats; Healthcare Systems; Histopathologic Grade; Histopathology; Image; Imaging Techniques; Individual; Indolent; Information Systems; Kinetics; Laboratories; Learning; Lesion; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of prostate; Measures; Methods; Modeling; Multiparametric Analysis; Neoplasm Circulating Cells; Neoplasm Metastasis; Outcome; Pathologic; Patients; Performance; Predictive Value; Procedures; Process; Prostate; Prostatectomy; Protocols documentation; Publishing; Radiogenomics; Reporting; Research Personnel; Risk; Sampling; Scoring Method; Screening for Prostate Cancer; Serum; System; Techniques; Testing; Tissues; Tumor Volume; Universities; Urine; Validation; Vendor; Work; adverse outcome; base; blood-based biomarker; cancer risk; cohort; cost; deep learning; digital; early detection biomarkers; genomic signature; high risk; imaging biomarker; improved; macrophage; men; novel; overtreatment; prognostic; prospective; prostate biopsy; prostate lesions; quantitative imaging; radiomics; reconstruction; rectal; risk stratification; tool; tumor; tumor heterogeneity; ultrasound; urinary

Abstract Oversampling and overdiagnosis of prostate cancer are significant management and cost issues that burden our health care system and the individual at risk with unnecessary biopsies and potential complications. The proposed studies will validate recent advances in quantitative prostate multiparametric MRI (mpMRI) techniques, blood biomarkers of aggressive prostate cancer and radiogenomics that relate to increased aggressive cancer risk by our group and collaborators. The overarching goal is to increase the negative predictive value (NPV) for significant prostate cancer and consequently reduce unnecessary biopsies. Central to the proposal are key collaborations between investigators from the Consortium for Imaging and Biomarkers (CIB), Early Detection Research Network (EDRN), and Jet Propulsion Laboratories (JPL). Novel automated techniques for quantitative analysis of mpMRI that identify prostate habitats at risk of harboring significant prostate cancer (Gleason score 3+4 and above or Grade Group (GG)2+) will be combined with improvements in mpMRI-ultrasound fusion biopsies. Our automated pixel-by-pixel 3D prostate habitat risk scoring (HRS) system is superior to the standard prostate lesion classification system, PIRADSv2, and is hypothesized to improve the Negative Predictive Value (NPV) for significant GG2+ cancers (Aim 1). Radiomics will be applied in Aim 1 to refine HRS in the University of Miami MDSelect protocol of 250 men (discovery=150; validation=100). Just as PIRADSv2 is suboptimal because it does not incorporate quantitative imaging information in risk stratification, models of risk based only on histopathologic grading ignore the underlying genomic determinants of outcome. We have shown that radiomics features are associated with underlying gene expression markers of adverse outcome. We propose in Aim 2 to apply newer criteria that incorporate Decipher® score with clinical-pathologic factors to improve the identification of aggressive prostate cancer. Radiomic features associated with these published criteria, termed the Spratt criteria, will improve the NPV for nonaggressive prostate cancer in the MDSelect cohort. We will also collaborate with investigators involved in the EDRN ID-430 clinical trial to test our models in a cohort (n=200) in a less rigorously controlled multi-institutional group with more variability in imaging techniques, vendors and machines. There is also opportunity to further improve risk classification through the analysis of blood-based markers (Aim 3) such as 4Kscore, circulating tumor cells (CTCs) and circulating cancer associated macrophage like (CAML) cells that are early biomarkers of aggressive cancer. The proposed work will test the incremental benefit of adding these serum-based biomarkers to improve the NPV models for significant prostate cancer.

摘要 前列腺癌的过度抽样和过度诊断是重大的管理和成本问题， 给我们的医疗保健系统和处于危险中的个人带来不必要的活检和潜在的并发症。 拟议的研究将验证定量前列腺多参数磁共振成像(Mpmri)的最新进展。 侵袭性前列腺癌的技术、血液生物标记物和与升高相关的放射基因组学 我们团队及其合作者的侵略性癌症风险。最重要的目标是增加负面影响 对重大前列腺癌的预测价值(NPV)，从而减少不必要的活检。中环 该提案的关键合作是来自成像和生物标记物联盟的研究人员之间的合作 (CIB)、早期探测研究网络(EDRN)和喷气推进实验室(JPL)。 用于定量分析mpMRI的新自动化技术，以识别有前列腺癌风险的前列腺栖息地 患有严重前列腺癌(Gleason评分3+4及以上或分级组(GG)2+)将被合并 随着mpMRI-超声融合活检的改进。我们的自动化逐像素3D前列腺栖息地风险 评分(HRS)系统优于标准的前列腺病变分类系统PIRADSv2，并且是 假设改善显著GG2+癌症的阴性预测值(NPV)(目标1)。放射组学 将在目标1中应用，以在迈阿密大学的MDSelect方案中完善250名男性的HRS(发现=150； 验证=100)。 正如PIRADSv2不是最优的，因为它不包含定量成像信息 风险分层，仅基于组织病理学分级的风险模型忽视了潜在的基因组 结果的决定因素。我们已经证明放射组学特征与潜在的基因有关。 不良结局的表达标志物。我们在目标2中建议采用更新的标准，包括 结合临床病理因素的Decpher®评分，以提高侵袭性前列腺癌的识别能力。 与这些公布的标准相关的放射学特征，称为斯普拉特标准，将改善 MDSelect队列中的非侵袭性前列腺癌。 我们还将与参与EDRN ID-430临床试验的研究人员合作，测试我们的模型 在一个不那么严格控制的多机构组的队列中(n=200)，成像的可变性更大 技术、供应商和机器。 通过以血液为基础的分析，也有机会进一步改进风险分类 标记物(AIM 3)，如4KScore、循环肿瘤细胞(CTCs)和循环肿瘤相关 巨噬细胞样(CAML)细胞是侵袭性癌症的早期生物标志物。拟议中的工作将测试 添加这些基于血清的生物标记物以改进NPV模型的增量效益 前列腺癌。