Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT05380518 |
| Other study ID # |
CCR5616 |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
May 1, 2022 |
| Est. completion date |
October 1, 2024 |
Study information
| Verified date |
January 2022 |
| Source |
Royal Marsden NHS Foundation Trust |
| Contact |
Manolis Tsiknakis |
| Phone |
+30-2810-391690 |
| Email |
tsiknaki[@]ics.forth.gr |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Currently, in the clinical landscape of PCa, much of the AI work is limited to single-centre,
single AI-architecture analyses and critically, on small data sets. ProCAncer-I will create a
vast, diversified and multidisciplinary repository, fed by a large collection of mp-MRI. The
participating clinical partners will congregate mp-MRI and clinical data, retrospectively and
prospectively, from more than 17.000 PCa patients (11.000 retrospective and 6.000 prospective
mp-MRI cases), including baseline examinations and follow up studies to form the ProstateNET
dataset, counting more than 1.5 million image representations of the prostate (cancerous,
non-cancerous and benign cases).
ProCAncer-I aims to address the unmet clinical needs in PCa regarding precision diagnosis and
personalised disease management with a disruptive paradigm change in clinical research,
exploiting a novel multi centre collaboration, comprising a master-global model, boosted with
MRI and AI modelling methodology. ProCAncer-I will deal with both retrospective and
prospective data. Retrospective data will be collected and will be used to implement and
train AI algorithms by other partners of the Consortium. Similarly, prospective data will be
collected for the development of vendor specific models and external validation of AI models.
Description:
In Europe, prostate cancer (PCa) is the second most frequent type of cancer in men and the
third most lethal. Current clinical practices, often leading to overdiagnosis and
overtreatment of indolent tumors, suffer from lack of precision.
This calls for advanced Artificial Intelligence (AI) models to decipher non-intuitive,
high-level medical image patterns and increase performance in discriminating indolent from
aggressive disease early on. This extends to these models also predicting recurrence,
detecting metastases and predicting the effectiveness of therapies. To date, efforts in this
field are fragmented, based on single-institution, size-limited and vendor-specific datasets
while available PCa public datasets are only a few hundred cases, making model
generalisability impossible.
The ProCAncer-I project brings together 13 partners (the consortium), including The Royal
Marsden NHS Foundation Trust (RMH), PCa centers, world leaders in AI and innovative
enterprises with recognised expertise in their respective domains. The objective is to
design, develop and sustain a cloud-based, secure European Image Infrastructure with tools
and services for data handling. The platform hosts the largest collection of PCa
multi-parametric Magnetic Resonance Imaging (mpMRI) scans and anonymised image data worldwide
with more than 17,000 cases, based on retrospective and prospective data from the consortium
in line with EU legislation (GDPR).
Robust AI models will be developed, based on novel learning methodologies, leading to AI
models that will address nine PCa clinical scenarios. To accelerate the clinical adoption of
PCa AI models, the project focuses on improving the trust in the AI solutions with respect to
fairness, safety, explainability and reproducibility. Metrics to monitor model performance
are being developed to further increase clinical trust and inform on possible failures and
errors, hopefully validating the effectiveness of AI-based models for clinical decision
making.
