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  • Radiology, Oncology, Quantitative Imaging Converge to Advance Precision Medicine

    Radiology is partnering with other specialties to develop new precision imaging techniques to advance patient care. By Mike Bassett

    October 1, 2017

    As precision medicine moves patients toward targeted therapies and treatment, cross-disciplinary collaboration is becoming more vital than ever. But that raises the question: who are radiology’s natural partners in this process?

    According to Peter L. Choyke, MD, director of the Molecular Imaging Program at the National Cancer Institute’s (NCI) Center for Cancer Research, the most obvious partnership is with oncology.

    “For example the new targeted immunotherapy drugs only work about 20 percent of the time, and it is very unclear which patients will respond,” said Dr. Choyke, a member of RSNA’s Molecular Imaging Committee.

    For that reason, methods are needed to best select patients who will respond to a particular therapies. And for patients who do respond, decisions need to be made about the duration or the aggressiveness of the response to a therapy.

    “Imaging could play a big role in selecting patients who would be good candidates for specific cancer therapy, and in monitoring the intensity of the response after those therapies,” he said.

    He pointed to the development of PD-L1 pathway inhibitors, which are changing the landscape of cancer. By binding to its receptors, antiPDantiPD-L1 antibodies reduces induce cytotoxic T-cell activity, proliferation and cytokine production which kill cancer cells.

    “One of the goals of these therapies is to activate T cells against a tumor, yet there is no really good way to measure T-cell activation,” he said. “So researchers are developing imaging agents that can show activated T-cell populations after checkpoint inhibitor therapy.”

    The convergence of radiology, pathology and genomics will also play a key role in the future of precision medicine — particularly that of precision cancer care. Dr. Choyke pointed out that pathologists — like radiologists — must deal with issues related to “information density” and the need to compress a good deal of information into a few words.

    “You can have a two-centimeter prostate cancer and the entire description will be a Gleason score and nothing else,” he said. “So you can see how much information is left on the slide.

    “But if you take an MRI and the pathology and then determine specific areas in the pathology that are correlated with bad outcomes and then determine the genomic mutations within those regions, you can predict through imaging which patients are likely to have worse outcomes,” Dr. Choyke said.

    In prostaste cancer, for example, researchers are working to correlate imaging with digital pathology; not just Gleason grading, but feature analysis of digital pathology that can be correlated with specific areas that have been selected for genomic testing.

    This database can then be used to develop deep learning methods that extract features not visible to radiologists, but that are nonetheless associated with higher risk cancers.

    “That is important because a physician will then know at a glance if a patient is at high risk for an aggressive tumor,” he added. “But it’s also important because a physician can direct a needle biopsy into that area and target the tissue more accurately and do genomics on the most aggressive part of the tumor.”

    Standardization Critical to Precision Medicine

    Another discipline poised to play a key role in personalized or precision medicine is quantitative imaging, which is critical to cancer care. There is a need for rapid development of quantitative imaging biomarkers for tumor diagnosis and prognosis to create better risk stratification and aid physicians in making personalized treatment decisions.

    But quantitative imaging faces a key challenge — the lack of standardization of imaging.

    To that end, RSNA’s Quantitative Imaging Biomarkers Alliance (QIBA) and the NCI’s Quantitative Imaging Network (QIN) are working to accelerate that progress by developing a standard of care for imaging practices that would also contribute to clinical trials.

    According to Daniel Sullivan, MD, a founding member of QIBA, clinical image acquisition must be standardized in order to reduce variability in clinical practice and clinical trials. Such quantification is important in reducing variability and increasing precision, particularly when compared to interpreting results qualitatively.

    “In order for standardized, objective, quantitative results to become accepted and expected in clinical practice, data from clinical trials needs to show that such objective results lead to better clinical decision-making and outcomes,” said Dr. Sullivan, professor emeritus in the Department of Radiology at Duke University Medical Center, Durham, NC, who now serves as QIBA’s external relations liaison.

    Therefore, clinical trials are important for implementing quantitative image acquisition parameters and demonstrating their value, he said.

    As both QIBA and QIN develop and collate data to validate the precision and utility of quantitative imaging biomarkers, radiologists, clinical trialists and ordering physicians will have more confidence in using them in clinical research and practice, Dr. Sullivan said.

    “Change always occurs slowly in medicine, so widespread implementation of quantitative imaging biomarkers for clinical decision-making will evolve gradually," Dr. Sullivan said.

    The issue of standardization also extends to standardizing the names and features of data elements in order to support comparative effectiveness research, precision medicine, radiomics, registry participation, machine learning, communication and public health.

    RSNA is working with the American College of Radiology (ACR) to define a set of common data elements (CDEs) for radiology reporting and decision support, according to Adam Flanders, MD, professor and co-director of the Department of Radiology, Division of Neuroradiology/ENT at Thomas Jefferson University Hospital in Philadelphia.

    While RSNA’s Reporting Initiative is designed to develop best reporting practices for radiology, the RSNA/ACR Joint Effort for Common Data Elements takes it one step further, said Dr. Flanders, who serves as chair of the RSNA Radiology Informatics Committee and is on the RSNA Steering Committee on Content for the Digital Roadmap.

    Each CDE represents a concept or feature with a controlled set of potential values. In neuroradiology, for example, if you are talking about a patient with a stroke, the question becomes, “What are the features that need to be described — whether quantitative or qualitative — and that should appear in a report so they can be understood by a human or mined very easily by a computer, and used to either drive therapeutic pathways or collect data on large-scale patient outcomes?” For this purpose, Dr. Flanders and colleagues are currently collaborating with the American Society of Neuroradiology to focus on reporting concepts specific to neuroradiology.

    “The whole idea is to collect the best practice features that exist for each disease entity and cofity what those features are,” Dr. Flanders said. “That supplements activities of both QIBA and QIN.”

    Precision Medicine Focus of RSNA 2017 Sessions

    Numerous precision medicine courses at RSNA 2017 focus on oncology and quantitative imaging, including:

    • “Research Opportunities Using the NIH: The Cancer Imaging Archive (TCIA) That Links Cancer Imaging to Clinical Data, Genomics, Proteomics, Quantitative Imaging and Deep Learning”
    • “Interrogating Tumor Heterogeneity Using Imaging”
    • “Multidisciplinary Communication in Cancer Care: Talking the Same Language”
    • “Special Interest Session: Translation of Quantitative Imaging from Clinical Research to Clinical Practice: Why and How?”

    RSNA 2017 Annual Oration in Radiation Oncology

    Daphne A. Haas-Kogan, MD, will speak on “Personalized Medicine and Radiation Oncology,” in this year’s Annual Oration in Radiation Oncology,” at 1:30 p.m., Wednesday, Nov. 29 in the Arie Crown Theater.

    Add these and all RSNA 2017 courses to My Agenda at Meeting.RSNA.org.