Information about project titled 'Reliability of MRI classification of hamstring injuires'
Reliability of MRI classification of hamstring injuires
|Details about the project - category||Details about the project - value|
|Project manager:||Arnlaug Wangensteen|
|Supervisor(s):||Johannes Tol, Roald Bahr|
|Coworker(s):||Robbart van Linschoten, Rodney Whitely, Bruce Hamilton, Erik Witvrouw, Emad Almusa, Mohammed Farooq, Sirine Boukarroum|
Acute hamstring muscle injuries represent the most prevalent non-contact muscle injury reported in sports with high speed running and power involved or in dancers due to the extreme requirements on range of motion. Despite the high prevalence and a rapidly expanding body of literature investigating acute hamstring muscle injuries, the incidence and re-injury rates have not improved over the last three decades, causing a significant loss of time from competition. The diagnosis and prognosis of time to return to sports (RTS) after acute hamstring injuries are mainly based on clinical findings from patient history and clinical examinations, supplemented by radiological examinations, such as magnetic resonance imaging (MRI) or ultrasound. However, the most accurate diagnostic and prognostic algorithm of clinical evaluation and radiological imaging is still unknown.
To investigate the intra- and inter reliability of three different MRI classifications for acute hamstring injuries and the predictive value of each of these MRI classifications on the time to RTS after acute hamstring injuries.
Male athletes, 18-50 years of age, sustaining a posterior thigh injury (potential hamstring strain) are recruited at the walk-in clinic at Aspetar where they undergo a standardized assessment procedure including patient history, clinical examinations and MRI.
In study III, MR images of 40 athletes with clinical signs of acute injury are assessed and scored by two independent radiologists (blinded for the clinical status of the patients) using a standardised scoring form including three different MR grading/classification systems, and Kappa statistics are performed to investigate the intra- and inter-tester reliability. Further, the predictive value of each of these MR grading/classification systems are investigated for the time to RTS.