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Pilot on Remote AutomatiC ulTrasound scan analysIs for hemophiliC patiEnts

Introduction to the pilot


People with hemophilia may experience joint bleeding, which can result in permanent joint damage if not properly treated.


Presently, the diagnosis of joint bleeding relies on ultrasound imaging, necessitating a physical visit to a specialized center. This limitation poses a hindrance to early detection.


We are developing a solution that enables patients and caregivers to acquire ultrasound images at home. These images can then be remotely diagnosed by healthcare practitioners.

Overall Objective

To enable the remote diagnosis of joint bleeding, providing a faster and more convenient diagnostic process for patients while reducing costs for the healthcare system.


Hemophilic patients
in Italy
Hemophilic patients
in Europe [*]
Euro spent on drugs for each patient yearly [*]
Cost of each remote ultrasound system (euro)

System components

The patient or caregiver can acquire ultrasound images at home using a portable ultrasound probe connected to a mobile PC. However, acquiring high-quality ultrasound images can be challenging and often requires extensive training. To simplify the process for patients or caregivers, we are developing the GAJA app, which leverages machine learning models to provide guidance during the image acquisition process.


Once the practitioners receive the acquired images, their role is to provide a diagnosis. To expedite the procedure and enhance diagnostic accuracy, we are developing CADET, a specialized computer-aided diagnosis tool. CADET leverages advanced machine learning models to prioritize interventions and intelligently reorganize the received images. Additionally, CADET autonomously identifies conditions like joint distention, providing valuable assistance to practitioners during the diagnostic process.

COD20 is a telemedicine platform. Our goal is to integrate the GAJA and CADET systems with COD20 to facilitate system scalability and provide functions such as visit bookings and diagnosis storage.

COD20 Logo


Kick-off meeting
Fall 2022
The PRACTICE project starts

The multidisciplinary team meets to define the project schedule and specific objectives. The team starts analyzing the problem and the possible solutions in detail.

Automatic detection of recess distention
Winter 2022
The first CADET tool is ready

Our team has trained a machine learning model that is capable of identifying distended joint recesses in ultrasound images. Since joint recess distention can be caused by hemarthrosis, this a first tool to support the remote diagnosis of hemarthrosis.

Supporting acquisition of ultrasound images
Spring 2023
A first GAJA prototype

Our team developed a first prototype of a system A first prototype of t system is ready. It supports the patient (or their caregivers) to acquire ultrasound joint images.

Summer 2023
GAJA evaluation with patients starts

After receiving the approval from the Ethical Committee, the research team will start experimenting the GAJA app with the patients. The aim is to evaluate whether the patients (or their caregivers) are able to acquire ultrasound images that can be used for hemarthrosis diagnosis.

Automatic detection of joint bleeding
Advanced CADET tools

CADET will include tools for intervention prioritization and automatic evaluation of joint bleeding

Improving the acquisition of ultrasound images
Second GAJA prototype

Based on the result of the first round of tests, GAJA is improved with enhanced user experience and additional functionalities, like automatic detection of unsuitable images.

COD20 integration
Toward an engineered system

CADET and GAJA will be integrated with COD20, providing new functions, like automatic visit booking.


Flora Peyvandi

Pilot Co-Leader
Dept. of Pathophysiology and Transplantation

Sergio Mascetti

Pilot Co-Leader
Dept. of Computer Science

Roberta Gualtierotti

Dept. of Pathophysiology and Transplantation

Claudio Bettini

Dept. of Computer Science

Dragan Ahmetovic

Dept. of Computer Science

Gabriele Civitarese

Dept. of Computer Science

Sara Arcudi

Dept. of Pathophysiology and Transplantation

Marco Colussi

Dept. of Computer Science

Aiman Solyman

Dept. of Computer Science


Ultrasound evaluation of hemophilic arthropathy: a proposal of definitions in a changing landscape, Gualtierotti, Roberta, Luigi Piero Solimeno, Flora Peyvandi, Andrea Giachi, Sara Arcudi, Alessandro Ciavarella, and Simona Maria Siboni, Research and Practice in Thrombosis and Haemostasis, 2024 Publication

GAJA - Guided self-Acquisition of Joint ultrAsound images, Marco Colussi, Sergio Mascetti, Dragan Ahmetovic, Gabriele Civitarese, Marco Cacciatori, Flora Peyvandi, Roberta Gualtierotti, Sara Arcudi, Claudio Bettini, International Workshop on Advances in Simplifying Medical Ultrasound (ASMUS 2023 (MICCAI Workshop)), 2023 Publication

A Computer-Aided Diagnosis Tool for the Detection of Hemarthrosis By Remote Joint Ultrasound in Patients with Hemophilia, Gualtierotti, R., Arcudi, S., Ciavarella, A., Colussi, M., Mascetti, S., Bettini, C., & Peyvandi, F. , Blood, 140(Supplement 1), 464-465., 2022 Publication

Ultrasound Detection of Subquadricipital Recess Distension, Colussi, M., Civitarese, G., Ahmetovic, D., Bettini, C., Gualtierotti, R., Peyvandi, F., & Mascetti, S., Intelligent Systems with Applications, 200183., 2023 Publication