The role of clinical imaging in oncology drug development: progress and new challenges

In 2008, the role of clinical imaging in oncology drug development was reviewed. The review outlined where imaging was being applied and considered the diverse demands across the phases of drug development. A limited set of imaging techniques was being used, largely based on structural measures of disease evaluated using established response criteria such as response evaluation criteria in solid tumours. Beyond structure, functional tissue imaging such as dynamic contrast-enhanced MRI and metabolic measures using [18F]flourodeoxyglucose positron emission tomography were being increasingly incorporated. Specific challenges related to the implementation of imaging were outlined including standardisation of scanning across study centres and consistency of analysis and reporting. More than a decade on the needs of modern drug development are reviewed, how imaging has evolved to support new drug development demands, the potential to translate state-of-the-art methods into routine tools and what is needed to enable the effective use of this broadening clinical trial toolset. In this review, we challenge the clinical and scientific imaging community to help refine existing clinical trial methods and innovate to deliver the next generation of techniques. Strong industry-academic partnerships and pre-competitive opportunities to co-ordinate efforts will ensure imaging technologies maintain a crucial role delivering innovative medicines to treat cancer.

A novel read methodology to evaluate the optimal dose of 68Ga-satoreotide trizoxetan as a PET imaging agent in patients with gastroenteropancreatic neuroendocrine tumours: a phase II clinical trial

BACKGROUND

⁶⁸Ga-satoreotide trizoxetan is a novel somatostatin receptor antagonist exhibiting higher tumour-to-background ratios and sensitivity compared to ⁶⁸Ga-DOTATOC. This randomised, 2 × 3 factorial, phase II study aimed to confirm the optimal peptide mass and radioactivity ranges for ⁶⁸Ga-satoreotide trizoxetan, using binary visual reading. To that end, 24 patients with metastatic gastroenteropancreatic neuroendocrine tumours received 5-20 µg of ⁶⁸Ga-satoreotide trizoxetan on day 1 of the study and 30-45 µg on day 16-22, with one of three gallium-68  radioactivity ranges (40-80, 100-140, or 160-200 MBq) per visit. Two ⁶⁸Ga-satoreotide trizoxetan PET/CT scans were acquired from each patient post-injection, and were scored by experienced independent blinded readers using a binary system (0 for non-optimal image quality and 1 for optimal image quality). For each patient pair of ⁶⁸Ga-satoreotide trizoxetan scans, one or both images could score 1.

RESULTS

Total image quality score for ⁶⁸Ga-satoreotide trizoxetan PET scans was lower in the 40-80 MBq radioactivity range (56.3%) compared to 100-140 MBq (90.6%) and 160-200 MBq (81.3%). Both qualitative and semi-quantitative analysis showed that peptide mass (5-20 or 30-45 µg) did not influence ⁶⁸Ga-satoreotide trizoxetan imaging. There was only one reading where readers diverged on scoring; one reader preferred one image because of higher lesion conspicuity, and the other reader preferred the alternative image because of the ability to identify more lesions.

CONCLUSIONS

Binary visual reading, which was associated with a low inter-reader variability, has further supported that the optimal administered radioactivity of ⁶⁸Ga-satoreotide trizoxetan was 100-200 MBq with a peptide mass up to 50 µg. Trial registration ClinicalTrials.gov, NCT03220217. Registered 18 July 2017, https://clinicaltrials.gov/ct2/show/NCT03220217.

Volume-based response evaluation with consensual lesion selection: a pilot study by using cloud solutions and comparison to RECIST 1.1

RATIONALE AND OBJECTIVES

Lesion volume is considered as a promising alternative to Response Evaluation Criteria in Solid Tumors (RECIST) to make tumor measurements more accurate and consistent, which would enable an earlier detection of temporal changes. In this article, we report the results of a pilot study aiming at evaluating the effects of a consensual lesion selection on volume-based response (VBR) assessments.

MATERIALS AND METHODS

Eleven patients with lung computed tomography scans acquired at three time points were selected from Reference Image Database to Evaluate Response to therapy in lung cancer (RIDER) and proprietary databases. Images were analyzed according to RECIST 1.1 and VBR criteria by three readers working in different geographic locations. Cloud solutions were used to connect readers and carry out a consensus process on the selection of lesions used for computing response. Because there are not currently accepted thresholds for computing VBR, we have applied a set of thresholds based on measurement variability (-35% and +55%). The benefit of this consensus was measured in terms of multiobserver agreement by using Fleiss kappa (κfleiss) and corresponding standard errors (SE).

RESULTS

VBR after consensual selection of target lesions allowed to obtain κfleiss = 0.85 (SE = 0.091), which increases up to 0.95 (SE = 0.092), if an extra consensus on new lesions is added. As a reference, the agreement when applying RECIST without consensus was κfleiss = 0.72 (SE = 0.088). These differences were found to be statistically significant according to a z-test.

CONCLUSIONS

An agreement on the selection of lesions allows reducing the inter-reader variability when computing VBR. Cloud solutions showed to be an interesting and feasible strategy for standardizing response evaluations, reducing variability, and increasing consistency of results in multicenter clinical trials.

US FDA draft Guidance Standard for Clinical Trial Imaging Endpoints: more than just imaging?

The current cost of developing a successful drug is typically over a billion dollars, with the registration trial(s) determining the success or failure of the entire development program. Often the primary endpoint of these trials is a subjective assessment. For registration trials with subjective endpoints, a regulatory agency may require a blinded independent central review (BICR) of the trial data. The BICR is a mechanism to reduce bias in open-labeled trials and to potentially increase accuracy and precision. A decision tree algorithm has been developed that can be used to determine when and what type of a BICR is needed. The US FDA draft Guidance Standard for Clinical Trial Imaging Endpoints can be used as an effective process map in exploring the value and use of BICRs in imaging, and in any hard to interpret variable subjective assessment in general.