Laurence P. Clarke

Imaging vascular function for early stage clinical trials using dynamic contrast-enhanced magnetic resonance imaging.

AbstractMany therapeutic approaches to cancer affect the tumour vasculature, either indirectly or as a direct target. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has become an important means of investigating this action, both pre-clinically and in early stage clinical trials. For such trials, it is essential that the measurement process (i.e. image acquisition and analysis) can be performed effectively and with consistency among contributing centres. As the technique continues to develop in order to provide potential improvements in sensitivity and physiological relevance, there is considerable scope for between-centre variation in techniques. A workshop was convened by the Imaging Committee of the Experimental Cancer Medicine Centres (ECMC) to review the current status of DCE-MRI and to provide recommendations on how the technique can best be used for early stage trials. This review and the consequent recommendations are summarised here. Key Points • Tumour vascular function is key to tumour development and treatment • Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can assess tumour vascular function • Thus DCE-MRI with pharmacokinetic models can assess novel treatments • Many recent developments are advancing the accuracy of and information from DCE-MRI • Establishing common methodology across multiple centres is challenging and requires accepted guidelines

Expanding the Use of Magnetic Resonance in the Assessment of Tumor Response to Therapy: Workshop Report

Although dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and magnetic resonance spectroscopy (MRS) have great potential to provide routine assessment of cancer treatment response, their widespread application has been hampered by a lack of standards for use. Thus, the National Cancer Institute convened a workshop to assess developments and applications of these methods, develop standards for methodology, and engage relevant partners (drug and device industries, researchers, clinicians, and government) to encourage sharing of data and methodologies. Consensus recommendations were reached for DCE-MRI methodologies and the focus for initial multicenter trials of MRS. In this meeting report, we outline the presentations, the topics discussed, the ongoing challenges identified, and the recommendations made by workshop participants for the use of DCE-MRI and 1H MRS in the clinical assessment of antitumor therapies.

The Reference Image Database to Evaluate Response to Therapy in Lung Cancer (RIDER) Project: A Resource for the Development of Change-Analysis Software

Critical to the clinical evaluation of effective novel therapies for lung cancer is the early and accurate determination of tumor response, which requires an understanding of the sources of uncertainty in tumor measurement and subsequent attempts to minimize their effects on the assessment of the therapeutic agent. The Reference Image Database to Evaluate Response (RIDER) project seeks to develop a consensus approach to the optimization and benchmarking of software tools for the assessment of tumor response to therapy and to provide a publicly available database of serial images acquired during lung cancer drug and radiation therapy trials. Images of phantoms and patient images acquired under situations in which tumor size or biology is known to be unchanged also will be provided. The RIDER project will create standardized methods for benchmarking software tools to reduce sources of uncertainty in vital clinical assessments such as whether a specific tumor is responding to therapy.

Challenges in image-guided therapy system design

System development for image-guided therapy (IGT), or image-guided interventions (IGI), continues to be an area of active interest across academic and industry groups. This is an emerging field that is growing rapidly: major academic institutions and medical device manufacturers have produced IGT technologies that are in routine clinical use, dozens of high-impact publications are published in well regarded journals each year, and several small companies have successfully commercialized sophisticated IGT systems. In meetings between IGT investigators over the last two years, a consensus has emerged that several key areas must be addressed collaboratively by the community to reach the next level of impact and efficiency in IGT research and development to improve patient care. These meetings culminated in a two-day workshop that brought together several academic and industrial leaders in the field today. The goals of the workshop were to identify gaps in the engineering infrastructure available to IGT researchers, develop the role of research funding agencies and the recently established US-based National Center for Image Guided Therapy (NCIGT), and ultimately to facilitate the transfer of technology among research centers that are sponsored by the National Institutes of Health (NIH). Workshop discussions spanned many of the current challenges in the development and deployment of new IGT systems. Key challenges were identified in a number of areas, including: validation standards; workflows, use-cases, and application requirements; component reusability; and device interface standards. This report elaborates on these key points and proposes research challenges that are to be addressed by a joint effort between academic, industry, and NIH participants.

Quantitative Imaging in Cancer Clinical Trials.

As anticancer therapies designed to target specific molecular pathways have been developed, it has become critical to develop methods to assess the response induced by such agents. Although traditional, anatomic CT, and MRI examinations are useful in many settings, increasing evidence suggests that these methods cannot answer the fundamental biologic and physiologic questions essential for assessment and, eventually, prediction of treatment response in the clinical trial setting, especially in the critical period soon after treatment is initiated. To optimally apply advances in quantitative imaging methods to trials of targeted cancer therapy, new infrastructure improvements are needed that incorporate these emerging techniques into the settings where they are most likely to have impact. In this review, we first elucidate the needs for therapeutic response assessment in the era of molecularly targeted therapy and describe how quantitative imaging can most effectively provide scientifically and clinically relevant data. We then describe the tools and methods required to apply quantitative imaging and provide concrete examples of work making these advances practically available for routine application in clinical trials. We conclude by proposing strategies to surmount barriers to wider incorporation of these quantitative imaging methods into clinical trials and, eventually, clinical practice. Our goal is to encourage and guide the oncology community to deploy standardized quantitative imaging techniques in clinical trials to further personalize care for cancer patients and to provide a more efficient path for the development of improved targeted therapies. Clin Cancer Res; 22(2); 284–90. ©2016 AACR.

Quantitative organ-uptake measurement.

Abstract A method has been developed for the quantitative assessment of organ radioactivity determined on the basis of external count-rate measurement. With use of a unique dual collimator system designed with depth-independent response throughout a scattering medium, in vivo organ activity can be evaluated to within ±9%. The system also allows for correction for active tissue backgrounds. The method was applied to quantitative assessment of splenic function on the basis of in vivo activity determination in 2 clinical cases in which splenectomy permitted an independent check.

New NCI initiatives in computer-aided diagnosis

The National Cancer Institute (NCI) is interested in supporting the development of an image database for lung cancer screening using spiral x-ray CT. A cooperative agreement is envisioned that will involve applications from investigators who are interested in joining a consortium of institutions to construct such a database as a public resource. The intent is to develop standards for generating the database resource and to allow this database to be used for evaluating computer aided diagnostic (CAD) software methods. Initial interest is focused on spiral CT of the lung because of the recent interest in using this imaging modality for lung cancer screening for patients at high risk, where early intervention may significantly reduce cancer mortality rates. The use of CAD methods is rapidly emerging for this large-scale cancer screening application as these methods have the potential of improving the efficiency of screening. Lung imaging is a good physical model in that it involves the use of 3D CAD methods that require critical software optimization for both detection and classification. In addition, the detection of change in the CT images over time, or changes in lung nodule size, has the potential to provide either improved early cancer detection or improved classification.

NCI initiative: Development of novel imaging technologies

T HE Biomedical Imaging Program (BIP) at the National Cancer Institute (NCI) from the National Institutes of Health (NIH) is initiating several new ways to support the biomedical imaging community. One initiative, known as a phased innovation award, is introduced in this editorial, and directed at development of novel imaging technology. This initiative is specifically tailored for technology developers. Significant advances in medical imaging technologies have been made over the last 25 years in such areas as magnetic resonance imaging (MRI), computed tomography (CT), nuclear medicine, and ultrasound. However, these advances largely focused on structural or anatomic imaging at the organ or tissue level. Furthermore, the research and development costs have traditionally been primarily borne by the medical device manufacturers. There is clearly a need and opportunity now to stimulate the development and integration of novel imaging technologies that exploit our current knowledge of the genetic and molecular bases of cancer. Those molecular biological discoveries have great implications for cancer prevention, detection and targeted therapy. Imaging technologies that can provide in vivo the same kind of cellular and molecular information that is currently available only fromin vitro techniques would be very useful. This is commonly referred to as in vivo molecular imaging. The stimulation of such technology development comes at a time when the resources of device and pharmaceutical manufacturers have diminished. Furthermore, their research and development efforts are often focused, for competitive reasons, toward improving patient throughput or making incremental improvements of existing technologies, rather than toward new high-risk technologies. The need for NCI support of bioengineering and technology development by academia and industry has been articulated in many NIH forums and NCI-supported workshops over the last two years [Imaging Sciences Working Group (ISWG) July 1997; Lung Imaging Workshop: Technology Transfer, Jan. 1997; Computer Aided Diagnosis and 3D Image Analysis, Oct. 1998; Quantitative In-Vivo Functional Imaging in Oncology, Jan. 1999; Focus Group on Magnetic Resonance Spectroscopy (MRS) in Clinical Oncology, April 1999; and BECON Symposium, June 1999.]. 1) The needs are to a) promote the development of very novel (high risk, high gain) technologies, including continued support for their maturation and full exploitation, b) promote system integration of technologies for targeted applications, and c) improve technology transfer by promoting partnerships between academia and industry.

WE‐B‐201B‐02: The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Public Database of CT Scans for Lung Nodule Analysis

PURPOSE: The LungImageDatabase Consortium (LIDC) was created by the National Cancer Institute to create a public database of annotated thoracic computed tomography(CT) scans as a reference standard for imaging research. This effort was augmented by the Foundation for the National Institutes of Health through the ImageDatabase Resource Initiative (IDRI). The LIDC/IDRI Database is intended to facilitate computer‐aided diagnosis(CAD) research for lung nodule detection, classification, and quantitative assessment. METHOD/MATERIALS: The LIDC/IDRI Database contains 1018 CT scans collected retrospectively from the clinical archives of seven academic institutions. Each scan was reviewed asynchronously by four thoracic radiologists through a two‐phase process. During the first “blinded read” phase, each radiologist independently reviewed the scans and marked lesions they identified according to one of three categories: “nodule ≥ 3 mm,” “nodule < 3 mm,” and “non‐nodule ≥ 3 mm.” The second “unblinded read” phase allowed each radiologist to review the marks of all other radiologists and confirm or modify their own marks. For any lesion that a radiologist marked as a “nodule ≥ 3 mm,” that radiologist constructed nodule outlines in every CT section in which the nodule appeared and provided subjective ratings of nodule characteristics such as subtlety, spiculation, solidity, and margin. The Database contains all images and radiologist marks for use by investigators. RESULTS: The Database contains 7371 lesions marked by at least one radiologist as either a “nodule ≥ 3 mm” or a “nodule < 3 mm.” 2669 lesions were marked by at least one radiologist as a “nodule ≥ 3 mm,” of which 777 (29.1%) were assigned such a mark by only a single radiologist, and 928 (34.8%) received such marks from all four radiologists.CONCLUSIONS: The LIDC/IDRI Database is expected to become a powerful resource as a reference standard for the medical imaging research community.