Teaching cancer imaging in the era of precision medicine: Looking at the big picture

Abstract

The role of imaging in cancer diagnosis and treatment has evolved at the same rapid pace as cancer management. Over the last twenty years, with the advancement of technology, oncology has become a multidisciplinary field that allows for researchers and clinicians not only to create individualized treatment options for cancer patients, but also to evaluate patients' response to therapy with increasing precision. Familiarity with these concepts is a requisite for current and future radiologists, as cancer imaging studies represent a significant and growing component of any radiology practice, from tertiary cancer centers to community hospitals. In this review we provide the framework to teach cancer imaging in the era of genomic oncology. After reading this article, readers should be able to illustrate the basics cancer genomics, modern cancer genomics, to summarize the types of systemic oncologic therapies available, their patterns of response and their adverse events, to discuss the role of imaging in oncologic clinical trials and the role of tumor response criteria and to display the future directions of oncologic imaging.

Keywords: Adverse events, clinical trials; Checkpoint inhibitors; Molecular targeted therapies; Oncologic imaging; Tumor response criteria.

Fig. 1

RAS pathway (A) and cancer genome landscape overview (B). (A) The RAS pathway is activated by EGF and EGF antibody binding to its receptor, EGFR. This binding leads to a signaling cascade which includes PI3K-RAS-mTORC and RAS-RAF-MEK ultimately leading to cell growth, proliferation, and migration. EGFR tyrosine kinase inhibitors (TKI) (gray burst), such as erlotinib, used for treatment of non-small cell lung cancer, and EGF antibodies, such as cetuximab (red burst), used for treatment of colorectal cancer, block the signaling cascade, ultimately halting cancer cell proliferation. (B) Cancer genome landscape overview. Multiple passenger mutations (blue array) and driver mutations (yellow rectangles) form the base of the triangle and will ultimately lead to cancer proliferation (short blue arrow) through multiple molecular pathways, including RAS pathway (red circle).(For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 2

72-year-old man with EFGR-mutated non-small cell lung cancer (NSCLC) who developed lung and bone metastases. Axial CT of the chest in lung window (A) shows a mass with spiculated morphology (dashed arrow) and associated pleural retraction (arrow). (B) Sagittal reconstructed image of the thoracic spine shows multiple sclerotic lesions (arrows), representing metastases from NSCLC. EGFR mutated NSCLC is associated with air bronchograms, pleural retraction, small lesion size, and absence of fibrosis, compared to EGFR-wild type NSCLC. In addition, this NSCLC subtype is associated with increased bone and lung metastases compared to ALK-mutated NSCLC.

Fig. 3

Patterns of response to immune checkpoint inhibitors, as initially described in patients with melanoma treated with ipilimumab. Images ABCD show four patterns of response, with change in tumor burden during treatment: (A) Steady decrease in tumor burden; (B) Stable disease followed by slow, steady decrease in tumor burden; (C) Response after initial increase in tumor burden; (D) Reduction in tumor burden after appearance of new lesions (dashed line).

Fig. 4

Pulmonary toxicity in a 50-year-old-man with metastatic melanoma on immune checkpoint inhibition. Axial CT chest performed before starting nivolumab and ipilimumab (two immune checkpoint inhibitors) shows small right middle and right lower lobe metastatic lung nodules (A) (arrows). CT performed three months after treatment with immune checkpoint inhibitors started shows consolidative opacity in the right middle lobe (B). Patient had shortness of breath and immune related pneumonitis was suspected. Prednisone taper was started and ipilimumab was stopped. Follow up CTs show residual ground glass changes in the middle lobe (C) and resolution of the lung nodules (D).

Fig. 5

Clinical trial design. Basket (A) and umbrella (B) protocols, two types of Master Protocols which allow for the evaluation of multiple treatments in different diseases (A) and evaluation of different treatments for the same disease (B). Master protocols facilitate recruitment of patients with rare genetic subtypes of a disease and allow a faster evaluation of treatment compared to randomized controlled clinical trials.

Fig. 6

Density changes in targeted therapy response. 75-year-old man with gastrointestinal stromal tumor metastatic to the liver. (A,B) Axial CT image performed before starting imatinib shows a hypodense liver lesion (arrow) with mean density of 63 Hounsfield Units. (C,D) Axial CT image performed three months after imatinib was started, shows similar size of the liver lesion but decreased attenuation of the lesion (arrow), with mean density of 33 Hounsfield Units.

Fig. 7

Choi criteria for assessing response to targeted therapy in metastatic GIST. 69-year-old man with gastrointestinal stromal tumor with metastatic disease to the liver being treated with sunitinib, a vascular endothelial growth factor inhibitor. (A) Axial CT image acquired during treatment with sunitinib shows multiple lesions in the liver, including a hypodense nonenhancing lesion in segment 4A (red circle). (B) Axial CT image acquired at next follow-up shows multiple enhancing mural nodules in the hypodense segment 4A lesion (arrow) reflecting disease progression. Per RECIST 1.1, this would be inaccurately categorized as stable disease as the lesions did not change in size, while per Choi criteria this would be correctly characterized as progressive disease.(For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 8

Treatment response evaluation using iRECIST criteria in a 76-year-old man with non-small cell lung cancer. CT of the chest (A) obtained before treatment with pembrolizumab was started shows a right lung nodule (arrow). Follow up CT of the chest (B) obtained 2 months after initiation of pembrolizumab shows increased size of the lesion (arrow), which decreased in size at follow-up CT obtained after 8 weeks (C), indicating pseudoprogression. iRECIST requires confirmation of progressive disease in 4–8 weeks to avoid misinterpreting pseudoprogression as true progression of disease, as mentioned in the accompanying chart.

Fig. 9

Radiogenomics: integration of imaging features, histopathologic data, genomics, and clinical data. CHIP: chromatin immunoprecipitation; SNP: Single nucleotide polymorphisms.