Skip to Content
COVID-19 Resources
Cancer Imaging Program (CIP)
Contact CIP
Show menu
Search this site
Last Updated: 09/21/17
Quantitative Imaging Network (QIN)

ECOG-ACRIN

ECOG-ACRIN-Based QIN Resource for Advancing Quantitative Cancer Imaging in Clinical Trials

MITCHELL D. SCHNALL, MD, PHD; DAVID MANKOFF, MD, PHD
PAUL E. KINAHAN, PHD; MARK ROSEN, MD, PHD
mitchell.schnall@uphs.upenn.edu; david.mankoff@uphs.upenn.edu; kinahan@uw.edu; Mark.Rosen@uphs.upenn.edu

Grant Number: U01CA190254

The goal of this project is to accelerate the development and deployment of quantitative imaging methods that improve the effectiveness and efficiency of clinical trials by using the combined resources of the NCI-sponsored cooperative group ECOG-ACRIN and the Quantitative Imaging Network (QIN).

As a resource, ECOG-ACRIN acts as a scientific site for evaluating methodologies and metrics for quality assurance of imaging and associated data, focusing on understanding the costs of efficient and effective site qualifications that result in high-quality imaging studies and the metrics required to appropriately define the number of participants required for adequate analysis.

Aim 1 of this project will evaluate quality control at QIN laboratories, comparing practices currently applied by the NCI (e.g., CQIE) and ACR Imaging Core Laboratory at each participating QIN site. Results from the Centers of Quantitative Imaging Excellence (CQIE) Program were analyzed and published [1.2] demonstrating the challenges in quality control standards for quantitative imaging in clinical research trials. The CQIE database was used to develop a database of QIN sites that is being used to create a site profile in the Qualification Utility for Imaging Clinical Trials (QUIC) of qualified QIN sites. This is intended to be dynamic as QIN sites change the QUIC dataset will be updated accordingly. This will form the basis of later studies in quality control standards within the QIN.

As part of Aim 2 of the project, ECOG-ACRIN will further act as a resource development platform working in conjunction with the Brown Statistical Center to develop datasets for method testing and validation from completed ACRIN research for assessment of QIN metrics and validation purposes. Outcomes and progression data will be made available for correlation with computational findings. A prioritized list of completed imaging trials with datasets that QIN sites felt were best positioned to support QIN development needs was established. Collaboration with NCI to develop standard guidelines and workflows for transferring the datasets to TCIA is underway.

Aim 3 of this project will leverage ECOG-ACRIN’s clinical trial development structure to enable prospective testing for methods developed by the QIN. ECOG-ACRIN will bring expertise across QIN Working Group platforms — in PET, MRI, CT, imaging statistical design, and informatics — to clinical trials by integrating quality assurance and QIN quantitative tools into prospective National Clinical Trial Network research. The National Clinical Trials Network (NCTN) will be a key focus for this effort to promote the use of more mature QIN tools in prospective multi-center clinical trials. This process has already been started through existing QIN sites that brought tools to bear in prior ACRIN studies focused on breast cancer, brain tumors, and prostate cancer, where QIN tools were applied to the analysis of MRI and PET. The EA QIN Resource initiated a more formal process in the form of a successful QIN-NCTN planning meeting that initiated ongoing discussions between NCTN oncologists and QIN imaging investigators. With the help of other QIN investigators who hold NCTN leadership positions, the EA leadership group worked with QIN staff to develop QIN sessions and discussions in the NCTNS groups on a rotating basis. At EA, emerging concepts in metastatic breast cancer imaging response assessment and prostate cancer diagnosis have exploratory Aims focused on QIN tools that are design to lead to prospective multi-center testing of QIN tools for this task. In addition to, these activities, EA QIN leadership has also played a key role in developing reviews of QI methods and the potential of the QIN for enhancing clinical trials that have bene published in high-impact oncology journals.

[1] Rosen M, et al. Academic Radiology. vol.24 (2):232-245, 2017. Performance Observations of Scanner Qualification of NCI-Designated Cancer Centers: Results From the Centers of Quantitative Imaging Excellence (CQIE) Program. PMID: 28395794.

[2] Scheuermann JS, et al. J Nucl Med. 58(7):1065-1071. 7 2017. doi: 10.2967/jnumed.116.186759. Epub 2017 Mar 2. Qualification of National Cancer Institute-Designated Cancer Centers for Quantitative PET/CT Imaging in Clinical Trials. PMID: 28254874.

Public Health Relevance Statement:

The evolution in our understanding of cancer requires an evolution in the design and implementation of clinical trials, and the quantitative imaging used to assess therapeutic efficacy. This was noted in the Institute of Medicine's influential report A National Cancer Clinical Trials System for the 21st Century, which stated that "the current structure and processes of the entire clinical trials system need to be redesigned to improve value by reducing redundancy and improving the effectiveness and efficiency of trials". The goal of this project is to accelerate the development and deployment of quantitative imaging methods that improve the effectiveness and efficiency of clinical trials by using the combined resources of the NCI-sponsored cooperative group ECOG-ACRIN and the Quantitative Imaging Network (QIN).

Project Terms:

Advisory Committees; American College of Radiology; American College of Radiology Imaging Network; Biological Markers; cancer cell; cancer clinical trial; cancer imaging; cancer therapy; Clinical Research; Clinical Trials; Clinical Trials Network; cost; Data; Data Reporting; Data Set; design; Development; Diagnostic; Disease; Eastern Cooperative Oncology Group; Effectiveness; Environment; Evaluation; Evolution; Goals; Image; Image Analysis; image archival system; imaging approach; imaging modality; imaging study; improved; Influentials; Informatics; Institute of Medicine (U.S.); Knowledge; Laboratories; Link; Magnetic Resonance Imaging; Malignant Neoplasms; Mediating; member; Metadata; Methodology; Methods; Modality; molecular oncology; Multicenter Trials; Mutation; National Clinical Trials Network; Network-based; novel; oncology; Outcome; Participant; Patients; Pharmaceutical Preparations; Positron-Emission Tomography; Process; prognostic; prospective; Prospective Studies; prospective test; Protocols documentation; public health relevance; quality assurance; Quality Control; Quantitative Evaluations; quantitative imaging; radiological imaging; Reporting; Research; Research Personnel; Resistance; Resource Development; Resources; response; Role; safety testing; Science; Services; Site; Source; Specific qualifier value; statistical center; Structure; System; Testing; Therapeutic; Time; tool; Translating; Treatment Efficacy; treatment response; Validation; Work; working group; X-Ray Computed Tomography