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. 2020 Nov;50(6):488-504.
doi: 10.1053/j.semnuclmed.2020.05.001. Epub 2020 Jun 10.

Imaging for Response Assessment in Cancer Clinical Trials

Anna G Sorace  1 , Asser A Elkassem  2 , Samuel J Galgano  3 , Suzanne E Lapi  4 , Benjamin M Larimer  3 , Savannah C Partridge  5 , C Chad Quarles  6 , Kirsten Reeves  7 , Tiara S Napier  7 , Patrick N Song  2 , Thomas E Yankeelov  8 , Stefanie Woodard  2 , Andrew D Smith  3
Affiliations

Imaging for Response Assessment in Cancer Clinical Trials

Anna G Sorace et al. Semin Nucl Med. 2020 Nov.

Abstract

The use of biomarkers is integral to the routine management of cancer patients, including diagnosis of disease, clinical staging and response to therapeutic intervention. Advanced imaging metrics with computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) are used to assess response during new drug development and in cancer research for predictive metrics of response. Key components and challenges to identifying an appropriate imaging biomarker are selection of integral vs integrated biomarkers, choosing an appropriate endpoint and modality, and standardization of the imaging biomarkers for cooperative and multicenter trials. Imaging biomarkers lean on the original proposed quantified metrics derived from imaging such as tumor size or longest dimension, with the most commonly implemented metrics in clinical trials coming from the Response Evaluation Criteria in Solid Tumors (RECIST) criteria, and then adapted versions such as immune-RECIST (iRECIST) and Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) for immunotherapy response and PET imaging, respectively. There have been many widely adopted biomarkers in clinical trials derived from MRI including metrics that describe cellularity and vascularity from diffusion-weighted (DW)-MRI apparent diffusion coefficient (ADC) and Dynamic Susceptibility Contrast (DSC) or dynamic contrast enhanced (DCE)-MRI (Ktrans, relative cerebral blood volume (rCBV)), respectively. Furthermore, Fluorodexoyglucose (FDG), fluorothymidine (FLT), and fluoromisonidazole (FMISO)-PET imaging, which describe molecular markers of glucose metabolism, proliferation and hypoxia have been implemented into various cancer types to assess therapeutic response to a wide variety of targeted- and chemotherapies. Recently, there have been many functional and molecular novel imaging biomarkers that are being developed that are rapidly being integrated into clinical trials (with anticipation of being implemented into clinical workflow in the future), such as artificial intelligence (AI) and machine learning computational strategies, antibody and peptide specific molecular imaging, and advanced diffusion MRI. These include prostate-specific membrane antigen (PSMA) and trastuzumab-PET, vascular tumor burden extracted from contrast-enhanced CT, diffusion kurtosis imaging, and CD8 or Granzyme B PET imaging. Further excitement surrounds theranostic procedures such as the combination of 68Ga/111In- and 177Lu-DOTATATE to use integral biomarkers to direct care and personalize therapy. However, there are many challenges in the implementation of imaging biomarkers that remains, including understand the accuracy, repeatability and reproducibility of both acquisition and analysis of these imaging biomarkers. Despite the challenges associated with the biological and technical validation of novel imaging biomarkers, a distinct roadmap has been created that is being implemented into many clinical trials to advance the development and implementation to create specific and sensitive novel imaging biomarkers of therapeutic response to continue to transform medical oncology.

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Figures

Figure 1:
Figure 1:
Serial diffusion-weighted (DW) MRI demonstrating good response in a 54-year-old woman who underwent neoadjuvant treatment for grade III triple-negative cancer in the I-SPY 2/ACRIN 6698 Multicenter Trial. a) Imaging was performed on a 3.0-T MRI scanner; shown are axial postcontrast dynamic contrast-enhanced (DCE) MRI images (left), non-contrast DW MRI (b value = 800 sec/mm2) images (center), and apparent diffusion coefficient (ADC) maps (right) for the pre-treatment and early-treatment (3 weeks after starting chemotherapy) time points. Tumor ADC was measured by defining a whole-tumor region of interest (ROI) across multiple slices (shown here for a representative slice, where the ROI was defined to avoid a central necrotic region) at each time point. b) Tumor ADC histograms demonstrate a substantial shift towards higher values with treatment, with mean tumor ADC increasing from 1.14 to 1.35 ×10−3 mm2/s (change in ADC = 18%). This patient experienced a pathologic complete response. Figure adapted from Partridge et al. ACRIN 6698 Primary Aim results. Radiology 2018 with permission.
Figure 2.
Figure 2.
The Liver Surface Nodularity (LSN) score adapted from CT is derived from 8 to 10 measurements of the anterior aspect of the left hepatic lobe where the liver is against visceral fat. This patient has advanced cirrhosis and hepatocellular carcinoma (white arrow). The high LSN score (4.3) suggest that patient is at high risk for post-operative complications.
Figure 3.
Figure 3.
Contrast-enhanced portal-venous CT images depict a liver metastasis from renal cell carcinoma on pre-therapy (left) and initial post-therapy (right) images. A freeform region of interest is used to segment the liver metastasis at both time points and depicts the vascular tumor burden (VTB, shaded red) and tumor necrosis (shaded green). The graphical report on the right depicts the liver metastasis and two lymph node metastases along with quantification of total tumor length, VTB and necrosis. Note that length decreased by only 21%, but the VTB decreased by 81%. These changes are predictive of a favorable response to therapy, and the patient had progression-free survival >2 years.
Figure 4.
Figure 4.
18F-FLT PET/CT scans shows early response to MDM2-inhibitor targeted therapy whereas the conventional CT scan images do not show any responses in a patient with EGFR-negative lung adenocarcinoma comparing baseline (prior to treatment) to 9 days post therapy. Circles indicate location of the tumor. As seen in the FLT-PET image, the tumor has marked decreases in signal, indicating decreased proliferation, however in the CT alone image, the anatomical size of the tumor has remained unchanged. Adopted from Kairemo et al. Diagnostics, 2020.
Figure 5.
Figure 5.
AI and machine learning algorithms are being developed to quantify therapeutic response in cancers and designed to implement into clinical workflow. Demonstration of (A) AI algorithms that assist with longitudinal tumor response assessment and (B) Demonstration of AI-assisted tumor reports are shown.
Figure 6.
Figure 6.
A 47-year-old woman with primary ER-positive, HER2-negative invasive ductal breast carcinoma and known metastases in the liver, nodes, and pleura. A, Axial CT and PET images from a contrast-enhanced FDG PET/CT through the chest demonstrate FDG-avid right pleural masses (SUVmax, 6.0; arrows). B, Axial CT and PET images from a non–contrast-enhanced 89Zr-trastuzumab PET/CT at the same level demonstrate 89Zr-trastuzumab avidity in the pleural lesions (SUVmax, 6.9; arrows). The pleural lesion was selected for biopsy as the lesion with the lowest risk for sampling. Biopsy of the pleural lesion demonstrated HER2 IHC of 2+ and FISH of 2.4. As FISH was greater than 2.0, this was considered a true-positive 89Zr-trastuzumab focus for a HER2-positive distant metastasis. Figure adapted from Ulaner, Lapi et al. Clinical Nuclear Medicine 2017 with permission.
Figure 7.
Figure 7.
Novel imaging biomarkers of therapeutic response in immunotherapy are being developed to target the expression and activation of immune cells that may predict therapeutic response, as well as the involvement of the tumor microenvironment such as vascularity and cellularity.
Figure 8.
Figure 8.
Workflow for development on new imaging biomarkers takes between 3–6 years from discovery to implementation into clinical trials. Novel radiopharmaceuticals for molecular imaging add additional time for toxicology studies prior to introduction into Phase 1 safety studies. Initial trials are typically introduced as integrated biomarkers to run parallel to therapeutic studies, prior to introduction of integrated metrics that guide treatment decision making.
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