The Power of Movement: Motion as an Imaging Endpoint

01 — Situation

Standard imaging endpoints were not capturing the full biological picture.

In early-phase clinical trials across multiple therapeutic areas, imaging is frequently used to quantify treatment response against established frameworks — RECIST in oncology, MaRIA and sMARIA scoring in Crohn’s disease, volumetric measures in renal and metabolic disease. These frameworks are well-validated and remain essential. But in programs where the mechanism of action involves tissue function, motility or dynamic organ behaviour, static structural measurement alone consistently underrepresents what is biologically occurring.

Across several early programs, Fidēs identified a recurring gap: sponsors were acquiring MRI data with the capacity to quantify movement — peristalsis, organ contraction, vascular pulsatility, respiratory motion — yet this dimension was being discarded during analysis. The biological signal was present in the data. It was simply not being extracted.

Movement can mean many things at a tissue or organ level; muscle contraction, peristalsis, vasomotion, cardiac motion, respiratory motion, gastric motility. Changes in movement are often the earliest indicators of changes in function.

The question Fidēs set out to answer was not whether movement mattered biologically — that was well-established in the literature — but whether it could be reliably quantified as an additive endpoint within standard early-phase imaging workflows, without requiring fundamentally different acquisition protocols.

02 — The Challenge

Why movement has been systematically ignored in standard endpoint frameworks.

The omission of movement as an imaging endpoint is not accidental — it reflects real analytical complexity. Standard endpoint frameworks were developed around static acquisition and structural quantification. Incorporating motion requires time-series image data, validated analysis pipelines for organ-specific motion patterns, and radiologist expertise in interpreting dynamic findings rather than single-frame structure.

For sponsors, this created a practical problem: even where motion data was present in the scan, there was no established pathway for incorporating it into endpoint reporting in a format that would satisfy regulatory and scientific scrutiny.

The secondary challenge was operational. Quality of life impacts from treatment — reduced gut motility, oesophageal peristalsis changes, uterine contractility — were being reported anecdotally by patients and investigators but lacked a quantitative imaging basis. Standard endpoint reporting had no mechanism to capture these signals, even when they were clearly present in the data.

03 — Our Solution

Integrating motion analysis as an additive endpoint within existing imaging workflows.

Fidēs applied Motilent’s validated GIQuant motion analysis pipeline — originally developed for quantitative GI motility assessment — as the basis for a broader motion quantification approach adaptable across organ systems. Critically, this did not require changes to acquisition protocols at site: existing cine-MRI sequences already present in standard GI and oncology protocols contained sufficient temporal resolution for motion extraction.

The approach delivered four categories of additive insight that standard endpoint reporting could not provide:

1. Normalised volumetric quantification

   By accounting for the position of a tumour or lesion across the full motion cycle, total volume measurements became substantially more reproducible between time points and between sites — reducing the measurement variability that contributes to noisy early-phase efficacy signals.

2. Secondary treatment impact — quality of life signals

   Changes in gut motility and oesophageal peristalsis — whether intended or otherwise — became quantifiable as secondary endpoints, giving sponsors an imaging basis for patient-reported QoL outcomes that previously had no objective correlate.

3. Structure characterisation over the motion cycle

   Rather than a single-frame structural assessment, tissue and organ structure could be characterised across the full cycle of movement — revealing functional relationships between structural change and dynamic behaviour that static measures cannot capture.

4. [Additional insight — scientific input pending]

   This section will be completed with input from the Fidēs scientific team. Placeholder for a fourth motion-based insight with therapy-area specific narrative.

All motion analysis was delivered within the Aperis platform alongside standard endpoint reads, giving sponsors a unified view of both the conventional and additive results — with full annotation and audit trail for regulatory review.

04 — Impact

Earlier, more confident go / no-go decisions — with a richer biological basis.

The integration of motion analysis as an additive endpoint changed the nature of the scientific conversation between the Fidēs team and the sponsor’s translational group. Rather than endpoint reporting at formal milestones, continuous access to motion-corrected data via Aperis meant that emerging biological signals — both positive and negative — could be identified and discussed while there was still time to act on them.

The motion data showed us a secondary QoL signal three timepoints before it appeared in the patient-reported outcomes. That changed how we approached the dose optimisation discussion.

Across programs where motion analysis was applied, sponsors reported three consistent outcomes: improved measurement reproducibility at the site level, a richer biological basis for interim go / no-go reviews, and — in GI programs specifically — a quantitative foundation for QoL claims that had previously rested entirely on PRO instruments.

The case for motion as a systematic additive endpoint in early-phase imaging is now part of Fidēs’ standard study design conversation. It is not a replacement for established frameworks — it extends them in a direction that early- phase decision-making specifically requires.

Key Results

What the data showed