A risk management approach for imaging biomarker-driven clinical trials in oncology

Repeatability of Quantitative Imaging Features in Prostate Magnetic Resonance Imaging

Background: Multiparametric magnetic resonance imaging (mpMRI) has emerged as a non-invasive modality to diagnose and monitor prostate cancer. Quantitative metrics on the regions of abnormality have shown to be useful descriptors to discriminate clinically significant cancers. In this study, we evaluate the reproducibility of quantitative imaging features using repeated mpMRI on the same patients. Methods: We retrospectively obtained the deidentified records of patients, who underwent two mpMRI scans within 2 weeks of the first baseline scan. The patient records were obtained as deidentified data (including imaging), obtained through the TCIA (The Cancer Imaging Archive) repository and analyzed in our institution with an institutional review board-approved Health Insurance Portability and Accountability Act-compliant retrospective study protocol. Indicated biopsied regions were used as a marker for our study radiologists to delineate the regions of interest. We extracted 307 quantitative features in each mpMRI modality [T2-weighted MR sequence image (T2w) and apparent diffusion coefficient (ADC) with b values of 0 and 1,400 mm/s2] across the two sequential scans. Concordance correlation coefficients (CCCs) were computed on the features extracted from sequential scans. Redundant features were removed by computing the coefficient of determination (R 2) among them and replaced with a feature that had the highest dynamic range within intercorrelated groups. Results: We have assessed the reproducibility of quantitative imaging features among sequential scans and found that habitat region characterization improves repeatability in ADC maps. There were 19 T2w features and two ADC features in radiologist drawn regions (native raw image), compared to 18 T2w and 15 ADC features in habitat regions (sphere), which were reproducible (CCC ≥0.65) and non-redundant (R 2 ≥ 0.99). We also found that z-transformation of the images prior to feature extraction reduced the number of reproducible features with no detrimental effect. Conclusion: We have shown that there are quantitative imaging features that are reproducible across sequential prostate mpMRI acquisition at a preset level of filters. We also found that a habitat approach improves feature repeatability in ADC. A validated set of reproducible image features in mpMRI will allow us to develop clinically useful disease risk stratification, enabling the possibility of using imaging as a surrogate to invasive biopsies.

Integrating molecular nuclear imaging in clinical research to improve anticancer therapy

Effective patient selection before or early during treatment is important to increasing the therapeutic benefits of anticancer treatments. This selection process is often predicated on biomarkers, predominantly biospecimen biomarkers derived from blood or tumour tissue; however, such biomarkers provide limited information about the true extent of disease or about the characteristics of different, potentially heterogeneous tumours present in an individual patient. Molecular imaging can also produce quantitative outputs; such imaging biomarkers can help to fill these knowledge gaps by providing complementary information on tumour characteristics, including heterogeneity and the microenvironment, as well as on pharmacokinetic parameters, drug-target engagement and responses to treatment. This integrative approach could therefore streamline biomarker and drug development, although a range of issues need to be overcome in order to enable a broader use of molecular imaging in clinical trials. In this Perspective article, we outline the multistage process of developing novel molecular imaging biomarkers. We discuss the challenges that have restricted the use of molecular imaging in clinical oncology research to date and outline future opportunities in this area.

Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives

For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up. Disease detection and staging involve qualitative, subjective assessment of images, whereas for prognosis, progression or response, quantitative evaluation of the apparent diffusion coefficient (ADC) is required. Validation and qualification of ADC in multicentre trials involves examination of i) technical performance to determine biomarker bias and reproducibility and ii) biological performance to interrogate a specific aspect of biology or to forecast outcome. Unfortunately, the variety of acquisition and analysis methodologies employed at different centres make ADC values non-comparable between them. This invalidates implementation in multicentre trials and limits utility of ADC as a biomarker. This article reviews the factors contributing to ADC variability in terms of data acquisition and analysis. Hardware and software considerations are discussed when implementing standardised protocols across multi-vendor platforms together with methods for quality assurance and quality control. Processes of data collection, archiving, curation, analysis, central reading and handling incidental findings are considered in the conduct of multicentre trials. Data protection and good clinical practice are essential prerequisites. Developing international consensus of procedures is critical to successful validation if ADC is to become a useful biomarker in oncology.

KEY POINTS

• Standardised acquisition/analysis allows quantification of imaging biomarkers in multicentre trials. • Establishing "precision" of the measurement in the multicentre context is essential. • A repository with traceable data of known provenance promotes further research.

Diffusion-weighted (DW) MRI in lung cancers: ADC test-retest repeatability

PURPOSE

To determine the test-retest repeatability of Apparent Diffusion Coefficient (ADC) measurements across institutions and MRI vendors, plus investigate the effect of post-processing methodology on measurement precision.

METHODS

Thirty malignant lung lesions >2 cm in size (23 patients) were scanned on two occasions, using echo-planar-Diffusion-Weighted (DW)-MRI to derive whole-tumour ADC (b = 100, 500 and 800smm-2). Scanning was performed at 4 institutions (3 MRI vendors). Whole-tumour volumes-of-interest were copied from first visit onto second visit images and from one post-processing platform to an open-source platform, to assess ADC repeatability and cross-platform reproducibility.

RESULTS

Whole-tumour ADC values ranged from 0.66-1.94x10-3mm2s-1 (mean = 1.14). Within-patient coefficient-of-variation (wCV) was 7.1% (95% CI 5.7-9.6%), limits-of-agreement (LoA) -18.0 to 21.9%. Lesions >3 cm had improved repeatability: wCV 3.9% (95% CI 2.9-5.9%); and LoA -10.2 to 11.4%. Variability for lesions <3 cm was 2.46 times higher. ADC reproducibility across different post-processing platforms was excellent: Pearson's R2 = 0.99; CoV 2.8% (95% CI 2.3-3.4%); and LoA -7.4 to 8.0%.

CONCLUSION

A free-breathing DW-MRI protocol for imaging malignant lung tumours achieved satisfactory within-patient repeatability and was robust to changes in post-processing software, justifying its use in multi-centre trials. For response evaluation in individual patients, a change in ADC >21.9% will reflect treatment-related change.

KEY POINTS

• In lung cancer, free-breathing DWI-MRI produces acceptable images with evaluable ADC measurement. • ADC repeatability coefficient-of-variation is 7.1% for lung tumours >2 cm. • ADC repeatability coefficient-of-variation is 3.9% for lung tumours >3 cm. • ADC measurement precision is unaffected by the post-processing software used. • In multicentre trials, 22% increase in ADC indicates positive treatment response.

SPECT and PET radiopharmaceuticals for molecular imaging of apoptosis: from bench to clinic

Owing to the central role of apoptosis in many human diseases and the wide-spread application of apoptosis-based therapeutics, molecular imaging of apoptosis in clinical practice is of great interest for clinicians, and holds great promises. Based on the well-defined biochemical changes for apoptosis, a rich assortment of probes and approaches have been developed for molecular imaging of apoptosis with various imaging modalities. Among these imaging techniques, nuclear imaging (including single photon emission computed tomography and positron emission tomography) remains the premier clinical method owing to their high specificity and sensitivity. Therefore, the corresponding radiopharmaceuticals have been a major focus, and some of them like ^99mTc-Annexin V, ¹⁸F-ML-10, ¹⁸F-CP18, and ¹⁸F-ICMT-11 are currently under clinical investigations in Phase I/II or Phase II/III clinical trials on a wide scope of diseases. In this review, we summarize these radiopharmaceuticals that have been widely used in clinical trials and elaborate them in terms of radiosynthesis, pharmacokinetics and dosimetry, and their applications in different clinical stages. We also explore the unique features required to qualify a desirable radiopharmaceutical for imaging apoptosis in clinical practice. Particularly, a perspective of the impact of these clinical efforts, namely, apoptosis imaging as predictive and prognostic markers, early-response indicators and surrogate endpoints, is also the highlight of this review.