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Pawel Szaro

Adjunct Senior Lecturer

Department of Radiology
Mail
pawel.szaro@gu.se
Visiting address
Bruna stråket 11b V 2 SU/Sahlgrenska
41345 Göteborg
Postal address
Sahlgrenska Universitetssjukhuset
41345 Göteborg

About Pawel Szaro

About Pawel Szaro

Pawel Szaro is an Associate Professor of Musculoskeletal Radiology at the Department of Clinical 91̽»¨s, Sahlgrenska Academy, University 91̽»¨, and a consultant radiologist in the Department of Musculoskeletal Radiology at Sahlgrenska University Hospital, Gothenburg, Sweden.

My research focuses on advancing imaging diagnostics for tumors, traumatic injuries, including sports-related conditions, within the musculoskeletal system. I collaborate closely with clinicians, technicians, students, and experts from various research disciplines to push the boundaries of what imaging can achieve. Interested in learning more? Please feel free to contact me for additional information.

My current research projects

Joint Stability – Dynamic Magnetic Resonance Imaging (MRI)

Traditionally, imaging joint movement and stability with MRI has been challenging due to motion artifacts. However, our research team has developed a new method for dynamic joint assessment using MRI. By collaborating with medical physicists and MRI technicians, we have successfully addressed the limitations posed by motion. This innovation allows us to observe joint movement in MRI, enabling the evaluation of joint stability—an assessment that was previously not possible. This project aims to determine the diagnostic value of this new technique in injuries.

Bone Imaging Without Radiation – Synthetic Computed Tomography (CT)

Historically, bone imaging has primarily relied on CT scans and x-rays. However, our team has introduced technical advancements that allow us to generate images remarkably like CT scans using MRI, without the need for X-ray radiation. This novel approach not only provides a radiation-free alternative for bone imaging but also reduces the need for additional examinations. This project focuses on comparing CT-like images obtained from MRI with traditional CT scans to assess their diagnostic value.

Sport Imaging – reducing time to return to play after sport injury

Injuries to tendons, muscles, or ligaments often force athletes to pause their training. Accurate diagnosis is crucial for selecting the most effective treatment. Unfortunately, existing diagnostic methods can sometimes lack the specificity needed. This project aims to develop precise, objective methods for evaluating sports-related injuries to the shoulder, knee, and ankle, with the goal of improving patient outcomes and reducing the time needed for athletes to return to their sport.

Interventions in the Musculoskeletal System

Advanced imaging techniques can play a crucial role in diagnosing and treating musculoskeletal tumors, potentially reducing the need for extensive surgical interventions. However, current imaging methods may not always be specific enough, sometimes necessitating a biopsy. Biopsy of a lesion within the musculoskeletal system can be technically challenging and may yield non-diagnostic results. This project aims to explore how imaging studies can enhance biopsy success rates. Additionally, we will evaluate the effectiveness of minimally invasive, image-guided techniques in treating musculoskeletal tumors.

Improving Diagnostics of Musculoskeletal Tumors

This project seeks to minimize the need for biopsies in the evaluation of soft tissue tumors by utilizing advanced MRI techniques. Recent innovations in MRI can differentiate tumor types by analyzing water movement within tissues and detecting specific tumor biomarkers. While these techniques have shown promise in accurately characterizing tumors in the brain and liver, their application in soft tissue tumor assessment is not yet widespread due to a lack of comprehensive scientific studies. The goal is to evaluate the potential of these new techniques in diagnosing musculoskeletal tumors.

Artificial Intelligence in Radiology

The use of artificial intelligence (AI) in medicine is rapidly expanding. In radiology, AI has the potential to facilitate quicker and more accurate fracture detection. This project will assess the impact of AI on the accuracy and efficiency of fracture diagnosis.

My research group

The musculoskeletal research group includes radiology specialists, residents, technicians, radiographers, and students. Our team is actively involved in supervising PhD student and supervising undergraduate thesis projects (examensarbete).

Interested in our work or thinking about collaboration? We welcome inquiries and are always open to new members joining our research group. Please feel free to reach out!

Below is a list of some of my collaborators from Sahlgrenska University Hospital.

PhD students:

Khaldun Ghali Gataa, MD, radiologist (I'm the main supervisor)

Alex Alexiev, MD, radiology resident (I'm the main supervisor)

Nektarios Solidakis, MD, radiologist (I'm a co-supervisor)

Researchers:

Katarzyna Bokwa Dabrowska, PhD, MD, Postdoc, consultant radiologist

Andreia Miron, MD

Isaac Romanus, MD

Isa Sasic, MD, radiology resident

Michel Huuskonen, MD

Fatih Inci, MD, PhD, consultant radiologist

Medical students involved in my projects:

Gustav Lodeiro

Ivan Sundeman Lytsy

Johan Rindner

André Ragnevad

Muhammad Kader

91̽»¨ information:

pawel.szaro@gu.se

Department of Musculoskeletal Radiology

Sahlgrenska University Hospital

Göteborgsvägen 31,

431 80 Mölndal

+46313426857