Oncology

Augmented response endpoints and scientific rigour for early-phase solid tumour programs where standard RECIST measures do not tell the full story.

Why imaging demands a different approach.

Early-phase imaging is indication-specific. Fidēs designs endpoints around the biology your study needs to resolve.

Solid tumour oncology imaging depends in large part on a number of very well-established endpoints, with RECIST 1.1 continuing to play a central role in registration studies.

Advanced imaging is, however, increasingly important, particularly in early-stage trials, as sponsors seek to better characterise their drug’s impact on tumours and the tumour microenvironment.

Led by a network of radiology and oncology experts, Fides supports this work, and harnesses radiomics measures of functional imaging to support this enhanced insight, and to drive better decision-making at the early stage, and in the design of later-phase studies.

In addition to our support of standard endpoints such as:

– RECIST 1.1

– PERCITS

– mRECIST

– Choi Criteria

Fides, through its proprietary Aperis system, extends beyond these endpoints to support a range of exploratory endpoints across dimensions:

– Volumetry: Semi-automated calculation and comparison of total lesion volume over timepoints: Tumour volume can change greatly without a corresponding change in the RECIST 1.1 measure. Understanding these changes in volume can make a significant difference to the assessment of treatment response, and can change decision-making with respect to a compound;

– 3D Imaging: Tumour shape can be a strong indicator of tumour growth trajectory – the ability to visualize tumours over time in 3D allows for a detailed assessment of treatment response, and the likelihood of a tumour spreading;

– Texture analysis: Gaining a strong understanding of intratumour heterogeneity helps with predicting the prediction of tumour progression and patient trajectories. Fides can assess multiple vectors relevant to such assessment, such as:

o Skewness: A standardized measure of tumour heterogeneity;

o Kurtosis: Giving a measure of how densely and regularly packed a cellular environment is as a means to stratifying the grade of cancer;

o Entropy: Entropy maps (or “radiomic maps”) are applied to visualize structural variation on a voxel-by-voxel basis, allowing clinicians to accurately pinpoint tumor boundaries and identify distinct areas of necrosis

We design analysis pipelines based on the scientific questions the sponsor wishes to address, and have great flexibility in applying optimised radiomic measures in support of standard endpoints.