Global Challenges for Cancer Imaging

Abstract

Imaging plays many essential roles in nearly all aspects of high-quality cancer care. However, challenges to the delivery of optimal cancer imaging in both developing and advanced countries are manifold. Developing countries typically face dramatic shortages of both imaging equipment and general radiologists, and efforts to improve cancer imaging in these countries are often complicated by poor infrastructure, cultural barriers, and other obstacles. In advanced countries, on the other hand, although imaging equipment and general radiologists are typically accessible, the complexity of oncologic imaging and the need for subspecialists in the field are largely unrecognized; as a result, training opportunities are lacking, and there is a shortage of radiologists with the necessary subspecialty expertise to provide optimal cancer care and participate in advanced clinical research. This article is intended to raise awareness of these challenges and catalyze further efforts to address them. Some promising strategies and ongoing efforts are reviewed, and some specific actions are proposed.

Improving Cancer Diagnosis and Care: Patient Access to Oncologic Imaging Expertise

“…For nearly every tumor type, imaging informs care management-from establishing a diagnosis and determining a treatment plan to monitoring response and detecting treatment-related complications and recurrence. 3 An accurate cancer diagnosis-one that is both precise and complete-increasingly relies on complex oncologic imaging techniques and the integration of expert imaging interpretations with pathology findings that characterize the disease at both the tissue and molecular levels. As precision oncology care advances, a simple imaging report describing tumor presence, size, and location is no longer adequate for patient care.…”

“…In response, radiologists have developed, and are continuously refining, an array of more sophisticated methods to assess treatment response and toxicity. 3,4 For example, the Quantitative Imaging Network has fostered the development and clinical validation of quantitative imaging tools and methods to measure or predict tumor response to therapies in cancer clinical trials. 5,6 These methods, combined with new imaging techniques that offer both anatomic and biologic information for patient triage and response assessment, require specialized training and experience for their appropriate use and interpretation.…”

“…As reviewed by Schlemmer et al, 3 studies have repeatedly shown substantial rates of disagreementranging from 13% to 56%-between initial cancer imaging reports and second-opinion readings by The responsibility for the content of this article rests with the authors and does not necessarily represent the views of the National Academies of Sciences, Engineering, and Medicine, its committees, its sponsors, or its convening activities.…”

“…Out of the more than 240 radiology fellowships currently offered in the United States, only a handful (approximately five) are dedicated to oncologic imaging. 3 Furthermore, modern cancer imaging principles are not treated in depth in medical school or residency training, and few continuing medical education courses are dedicated to cancer imaging.…”

Artificial intelligence performance in detecting tumor metastasis from medical radiology imaging: A systematic review and meta-analysis

“…Artificial intelligence (AI) has already shown great promise to address this problem through automated diagnosis from medical imaging [ 8 , 9 ]. In the 1980s, artificial neural networks (ANNs) were developed [10] , resulting in a surge of machine learning (ML) based on statistical models.…”