Project 2: Non-invasive imaging metrics to optimize early treatment switching decisions and prognostic modeling of long-term outcomes

项目 2：非侵入性成像指标，用于优化早期治疗转换决策和长期结果的预后建模

• 批准号: 10628610
• 负责人: Nola M. Hylton-Watson
• 金额: $ 37.6万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-08 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10628610
• 关键词: Address; Algorithms; Area; Beds; Biological Markers; Biopsy; Breast; Breast Cancer Treatment; Breast Magnetic Resonance Imaging; Cancer Burden; Classification; Clinical; Clinical Drug Development; Core Biopsy; Data; Decision Modeling; Dedications; Disease; Disease-Free Survival; Drug Evaluation; ERBB2 gene; Early Diagnosis; Early treatment; Elements; Eligibility Determination; Endocrine; Estrogen receptor positive; Evaluation; Funding; Goals; Heterogeneity; Histopathology; Image; In complete remission; Individual; Kinetics; Label; Magnetic Resonance Imaging; Mammary Neoplasms; Measurement; Measures; Methodology; Modeling; Molecular; Negative Finding; Neoadjuvant Therapy; Nodal; Normal tissue morphology; Operative Surgical Procedures; Outcome; Pathologic; Pathology; Patients; Performance; Pharmaceutical Preparations; Phase; Positron-Emission Tomography; Probability; Prognostic Marker; Protocols documentation; Randomized; Recommendation; Regimen; Research Personnel; Residual Cancers; Retrospective Studies; Sequential Treatment; Serial Magnetic Resonance Imaging; Shapes; Signal Transduction; Standardization; Testing; Time; Training; Treatment Protocols; Tumor Volume; Tumor-Derived; Update; Widespread Disease; arm; biomarker development; cohort; contrast enhanced; design; drug development; drug efficacy; effectiveness evaluation; imaging biomarker; imaging modality; improved; individual patient; individualized medicine; malignant breast neoplasm; molecular marker; molecular subtypes; next generation; non-invasive imaging; novel; participant enrollment; patient subsets; personalized medicine; predicting response; predictive marker; predictive modeling; prognostic; prognostic model; programs; quantitative imaging; radiomics; radiotracer; relapse risk; response; response biomarker; success; targeted biomarker; tool; treatment arm; treatment effect; treatment response; trial design; tumor; tumor DNA; tumor heterogeneity; uptake

The overall objective of the Program Project is to optimize every patient’s likelihood of reaching a pathologic complete response (pCR) by using imaging, histopathology and molecular biomarkers to guide their treatment. Project 2 focuses on advancing the imaging methods in the evolved design of I-SPY2.2, to identify patients that might benefit from a change in course of treatment. In the I-SPY2 trial design, MRI measurements of functional tumor volume (FTV) are the biomarker used to inform the longitudinal model for evaluation of drug arms. In I-SPY2.2, FTV is used at the individual patient level to tailor treatments, raising the need for greater control over variability in MRI performance. We have been addressing many of the elements involved in standardization of MRIs performed in the clinical setting through NCI-funded efforts in the area of quantitative imaging. We also performed retrospective studies using data from 990 patients randomized to one of 9 experimental drug arms completed by 2016 to better understand the impact of variability on FTV’s performance as a biomarker and those findings have been used to introduce refinements to the I-SPY2 MRI exam protocol. Specific Aims 1 and 2 focus on iterative improvements to the de-escalation strategy and pre-RCB, as well as the escalation strategy, respectively. While FTV-based response provides the initial signal for considering a change in treatment, different strategies are required to improve the level of certainty for recommending escalation or de-escalation, given MRI’s relative strength in demonstrating extensive disease, and limitation in detecting minimal disease. In the pre-RCB de- escalation strategy, a negative finding on core biopsy of the tumor bed at 12-weeks is required before the option to omit AC is offered. In the scenario of escalation, we use MRI response of less than 30% at 3-weeks to flag potential poor response and recommend repeat imaging at 6-weeks, where the threshold for escalation to Block B is <65% FTV response. We will build on these initial strategies in several ways. Current MRI prediction models are based on data from the initial 990 patients enrolled under I-SPY2 and have been optimized within subtypes defined by HR and HER2. We will refine these models using the more biologically-relevant Response-Predictive Subtype schema and using expanded I- SPY patient cohorts. More comprehensive MRI prediction models twill be developed, integrating classifiers of shape, heterogeneity and normal tissue features that can be derived from the same MRI data used to measure FTV. Working with Project 3 investigators, we will pose the question of added value of ctDNA in both the de-escalation and escalation strategies, investigating the use of ctDNA at multiple timepoints. Specific Aim 3 addresses the potential additive benefit of serial FTV measurement to the histopathologic endpoint residual cancer burden (RCB) which has been well-established as prognostic in the neoadjuvant setting. Recognizing the unique setting of I-SPY 2 in which MRI is performed for all patients, and that serial MRI is not feasible in all clinical settings, we will specifically investigate the differential benefit by subtype and treatment arms to determine if there are sub-groups of patients for whom added prognostic information is particularly informative and MRI can be recommended. Specific Aim 4 will explore the use of imaging markers derived from 18F-fluoroestradiol (FES)dedicated breast PET for patients receiving endocrine treatment in an I-SPY2.2 substudy.

该项目的总体目标是优化每位患者达到病理完全的可能性