Medical images are used in many therapeutic areas and contain a goldmine of information. Part of this information is traditionally extracted by radiologists and with the advances made in image processing and artificial intelligence, computers are now able to go deeper in the extraction of almost every detail which is hidden in the image. 

Central Imaging Lab

Industry &
Pharma

In clinical trials, centralized and automated analysis of medical images allow the removal of human-induced variability and bias.

Next to the imaging data, the RadiomiX Toolbox allows to use clinical and genomic data together with target endpoints to build diagnostic and predictive models for disease progression and treatment response.
In clinical trials, centralized and automated analysis of medical images allow the removal of human-induced variability and bias.

 

Thanks to our extensive experience in handling medical imaging variability, applying AI and trial statistics, and working with pharma companies, our goal is to position Accentedge Health as the next generation imaging CRO. For this, Accentedge Health provides a full package of services.

QA

At Accentedge Health we are convinced that the quality of the medical imaging scans is fundamental for the success of the radiomics analysis and its subsequent interpretation.

Accentedge Health helps its clients during the setup of their trials to assure an optimal imaging acquisition protocol for high quality data. For this, we base ourselves on years of experience in quantifying variabilities in images coming from different imaging modalities, vendors, machines, acquisition parameters and reconstruction settings. Next to that, we are also developing our own CT-phantom, specifically designed for lung cancer research, with more planned to come.
Breast cancer classified into 12 unique biological groups
Timely Diagnosis

During the imaging analysis phase, Accentedge Health guarantees that every scan processed is free of patient identifiable information, contains the correct region of interest (ROI) and has been collected using the settings specified in the trial protocol. If multiple imaging visits exist in one trial, we guarantee that the follow-up images are from the same subject as the baseline imaging and that each quantification is performed on the exact same region of interest. If problems are identified, our team of expert radiologists and AI scientists will guide our clients through the available mitigation strategies.

Segmentation

The first step in the imaging analysis process is the delineation or segmentation of the region of interest (ROI). At Accentedge Health this action is performed both manually or in a fully automated manner on CT, MRI, PET and Rx images. All our manual segmentations are carried out by a team of trained staff members and the results are always validated by at least one board-certified radiologist.

Additionally, based on our ever-growing dataset of available and validated segmentations, our R&D team continuously builds automatic segmentation tools. These solutions can replace the manual segmentation once their accuracy is demonstrated to be non-inferior to a set of board-certified radiologists.

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Currently we have developed automatic segmentation tools for the following:
  • Liver, liver metastases and hepatocellular carcinoma (HCC)
  • Lungs, primary lung tumor
  • Kidney, renal cortex, cysts and metastasis
  • Heart (epicardium, endocardium and myocardium)
  • Inner ear labyrinth
And our R&D team is currently working on automatic segmentation tools for airways, pulmonary vasculature, vertebral column, gastric cancer, prostate cancer, brain cancer, breast cancer and head & neck cancer.

Radiomics

Our founders are the inventors of the word and concept of radiomics. Radiomics is a synonym for advanced image quantification and this is at the core of what we do at Accentedge Health. Based on the segmentation of the relevant region of interest, the radiomics analysis quantifies all the information contained in the medical images.

Next to the imaging data, the RadiomiX Toolbox allows to use clinical and genomic data together with target endpoints to build diagnostic and predictive models for disease progression and treatment response.
This quantification can be based on handcrafted or deep learning features. Handcrafted features are mathematical equations representing the size, shape, texture, and intensity of the region of interest. Deep learning features use neural networks to identify relevant characteristics of the ROI that cannot be defined upfront.

These features can be used as endpoint linked to the efficacy and safety of treatment and can be combined to predict disease presence, progression and therapeutic outcome.

Interpretation & Reporting

At Accentedge Health we know that data alone is not enough to lead to concrete solutions addressing the unmet medical needs of our clients. The high-resolution dataset generated by our radiomics analysis requires adapted trial statistics approaches. Therefore, our team of experienced data scientists and statisticians is specialized in guiding our clients during the trial data analysis steps, providing data interpretation, and reporting at different levels for scientific, executive, and market-oriented audiences. This will guarantee that data is used and presented in optimal ways, to make sure that our conclusions are insightful but not overly optimistic.

Model Accuracy
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