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LIVERPOOL, ENGLAND – The measurement of acoustic emissions and kinetic instability of the knee could become a promising noninvasive way to detect osteoarthritis (OA), according to a recent study.
Researchers at the University of Oulu (Finland) have developed a prototype device that allows multimodal assessment of the sound and motion of the knee.
“The OA diagnostic chain has many problems, some modalities are very expensive, and some have a low sensitivity as well,” said study investigator Aleksei Tiulpin, MSc, at the World Congress on Osteoarthritis, referring to magnetic resonance imaging, x-ray imaging, and symptomatic assessment, respectively.
The investigational device that the research team has developed is worn like a brace around the knee and has microphones embedded within it to capture sound coming from the right and left sides of the knee. The device also uses two accelerometers, one placed on the thigh and one on the lower limb to measure movement simultaneously.
“We developed all the software and all the hardware ourselves for this project,” Mr. Tiulpin noted at the congress, sponsored by the Osteoarthritis Research Society International. “The acoustic and kinematic information was measured simultaneously.”
To see whether the prototype device was able to aid the diagnosis of OA, Mr. Tiulpin and his associates recruited 66 women aged 44-67 years old, roughly half of whom (51.5%) had radiographically confirmed knee OA of Kellgren-Lawrence grade 2 or higher.
The participants were asked to perform three exercise tests while wearing the device. First, they had to stand from a sitting position 10 times. Second, they were asked to extend the leg from the knee while sitting down (flexion-extension) 10 times. Third, and finally, they were asked to perform a one leg stand on the right leg twice.
For the acoustic data analysis, data from the standing phase of the sit-to-stand test and the extension phase of the flexion-extension tests were used. Mr. Tuilpin explained that the acoustic signals underwent processing to segment and filter them into candidate locations. The average sound patterns seen in the candidate locations were then analyzed, then a consistency analysis was undertaken. With this approach, inconsistent patterns of knee crepitation could be captured, Mr. Tiulpin explained.
Kinematic signals received from the movement sensors were used to determine the degree of knee instability. Higher signal magnitudes could potentially indicate stability problems, which can be quantified using signal power, Mr. Tiulpin’s slides stated.
A variety of statistical calculations were made to see how well the device might predict OA changes, and a model combining body mass index and age had an area under the curve of 84%, which suggested that it might be possible to improve OA detection with the addition of the device versus BMI and age alone.
“Our results indicated highly promising applications of the method,” Mr. Tiulpin suggested.
These findings are “very interesting,” commented one of the moderators of the session, Erwin van Spil, MD, of University Medical Center Utrecht (The Netherlands) as he opened up the floor to questions.
“I’ve had this question for years … what causes the clicks?” one delegate asked Mr. Tiulpin during discussion. He responded that it could be down to many things, one of which is cartilage components grinding against each other.
Dr. Spil, who was not involved in the study, commented in an interview that using acoustics in the detection of knee OA was still quite a novel concept. “It’s noninvasive, which is quite unique in our general approach, and it might enable an early diagnosis of OA, which is what we are aiming for.”
Although the study did have control subjects, it’s not clear at this point whether very early OA was being assessed, Dr. Spil suggested. “We did not have the opportunity to ask about the OA characteristics. I think they had radiographic OA, but we don’t know the grade and we were not informed about the clinical situation, so we don’t know if anyone had pain, for example.”
Mr. Tiulpin did not have any conflicts of interest to disclose.
SOURCE: Tiulpin A et al. Osteoarthritis Cartilage 2018;26(1):S40–S41.
LIVERPOOL, ENGLAND – The measurement of acoustic emissions and kinetic instability of the knee could become a promising noninvasive way to detect osteoarthritis (OA), according to a recent study.
Researchers at the University of Oulu (Finland) have developed a prototype device that allows multimodal assessment of the sound and motion of the knee.
“The OA diagnostic chain has many problems, some modalities are very expensive, and some have a low sensitivity as well,” said study investigator Aleksei Tiulpin, MSc, at the World Congress on Osteoarthritis, referring to magnetic resonance imaging, x-ray imaging, and symptomatic assessment, respectively.
The investigational device that the research team has developed is worn like a brace around the knee and has microphones embedded within it to capture sound coming from the right and left sides of the knee. The device also uses two accelerometers, one placed on the thigh and one on the lower limb to measure movement simultaneously.
“We developed all the software and all the hardware ourselves for this project,” Mr. Tiulpin noted at the congress, sponsored by the Osteoarthritis Research Society International. “The acoustic and kinematic information was measured simultaneously.”
To see whether the prototype device was able to aid the diagnosis of OA, Mr. Tiulpin and his associates recruited 66 women aged 44-67 years old, roughly half of whom (51.5%) had radiographically confirmed knee OA of Kellgren-Lawrence grade 2 or higher.
The participants were asked to perform three exercise tests while wearing the device. First, they had to stand from a sitting position 10 times. Second, they were asked to extend the leg from the knee while sitting down (flexion-extension) 10 times. Third, and finally, they were asked to perform a one leg stand on the right leg twice.
For the acoustic data analysis, data from the standing phase of the sit-to-stand test and the extension phase of the flexion-extension tests were used. Mr. Tuilpin explained that the acoustic signals underwent processing to segment and filter them into candidate locations. The average sound patterns seen in the candidate locations were then analyzed, then a consistency analysis was undertaken. With this approach, inconsistent patterns of knee crepitation could be captured, Mr. Tiulpin explained.
Kinematic signals received from the movement sensors were used to determine the degree of knee instability. Higher signal magnitudes could potentially indicate stability problems, which can be quantified using signal power, Mr. Tiulpin’s slides stated.
A variety of statistical calculations were made to see how well the device might predict OA changes, and a model combining body mass index and age had an area under the curve of 84%, which suggested that it might be possible to improve OA detection with the addition of the device versus BMI and age alone.
“Our results indicated highly promising applications of the method,” Mr. Tiulpin suggested.
These findings are “very interesting,” commented one of the moderators of the session, Erwin van Spil, MD, of University Medical Center Utrecht (The Netherlands) as he opened up the floor to questions.
“I’ve had this question for years … what causes the clicks?” one delegate asked Mr. Tiulpin during discussion. He responded that it could be down to many things, one of which is cartilage components grinding against each other.
Dr. Spil, who was not involved in the study, commented in an interview that using acoustics in the detection of knee OA was still quite a novel concept. “It’s noninvasive, which is quite unique in our general approach, and it might enable an early diagnosis of OA, which is what we are aiming for.”
Although the study did have control subjects, it’s not clear at this point whether very early OA was being assessed, Dr. Spil suggested. “We did not have the opportunity to ask about the OA characteristics. I think they had radiographic OA, but we don’t know the grade and we were not informed about the clinical situation, so we don’t know if anyone had pain, for example.”
Mr. Tiulpin did not have any conflicts of interest to disclose.
SOURCE: Tiulpin A et al. Osteoarthritis Cartilage 2018;26(1):S40–S41.
LIVERPOOL, ENGLAND – The measurement of acoustic emissions and kinetic instability of the knee could become a promising noninvasive way to detect osteoarthritis (OA), according to a recent study.
Researchers at the University of Oulu (Finland) have developed a prototype device that allows multimodal assessment of the sound and motion of the knee.
“The OA diagnostic chain has many problems, some modalities are very expensive, and some have a low sensitivity as well,” said study investigator Aleksei Tiulpin, MSc, at the World Congress on Osteoarthritis, referring to magnetic resonance imaging, x-ray imaging, and symptomatic assessment, respectively.
The investigational device that the research team has developed is worn like a brace around the knee and has microphones embedded within it to capture sound coming from the right and left sides of the knee. The device also uses two accelerometers, one placed on the thigh and one on the lower limb to measure movement simultaneously.
“We developed all the software and all the hardware ourselves for this project,” Mr. Tiulpin noted at the congress, sponsored by the Osteoarthritis Research Society International. “The acoustic and kinematic information was measured simultaneously.”
To see whether the prototype device was able to aid the diagnosis of OA, Mr. Tiulpin and his associates recruited 66 women aged 44-67 years old, roughly half of whom (51.5%) had radiographically confirmed knee OA of Kellgren-Lawrence grade 2 or higher.
The participants were asked to perform three exercise tests while wearing the device. First, they had to stand from a sitting position 10 times. Second, they were asked to extend the leg from the knee while sitting down (flexion-extension) 10 times. Third, and finally, they were asked to perform a one leg stand on the right leg twice.
For the acoustic data analysis, data from the standing phase of the sit-to-stand test and the extension phase of the flexion-extension tests were used. Mr. Tuilpin explained that the acoustic signals underwent processing to segment and filter them into candidate locations. The average sound patterns seen in the candidate locations were then analyzed, then a consistency analysis was undertaken. With this approach, inconsistent patterns of knee crepitation could be captured, Mr. Tiulpin explained.
Kinematic signals received from the movement sensors were used to determine the degree of knee instability. Higher signal magnitudes could potentially indicate stability problems, which can be quantified using signal power, Mr. Tiulpin’s slides stated.
A variety of statistical calculations were made to see how well the device might predict OA changes, and a model combining body mass index and age had an area under the curve of 84%, which suggested that it might be possible to improve OA detection with the addition of the device versus BMI and age alone.
“Our results indicated highly promising applications of the method,” Mr. Tiulpin suggested.
These findings are “very interesting,” commented one of the moderators of the session, Erwin van Spil, MD, of University Medical Center Utrecht (The Netherlands) as he opened up the floor to questions.
“I’ve had this question for years … what causes the clicks?” one delegate asked Mr. Tiulpin during discussion. He responded that it could be down to many things, one of which is cartilage components grinding against each other.
Dr. Spil, who was not involved in the study, commented in an interview that using acoustics in the detection of knee OA was still quite a novel concept. “It’s noninvasive, which is quite unique in our general approach, and it might enable an early diagnosis of OA, which is what we are aiming for.”
Although the study did have control subjects, it’s not clear at this point whether very early OA was being assessed, Dr. Spil suggested. “We did not have the opportunity to ask about the OA characteristics. I think they had radiographic OA, but we don’t know the grade and we were not informed about the clinical situation, so we don’t know if anyone had pain, for example.”
Mr. Tiulpin did not have any conflicts of interest to disclose.
SOURCE: Tiulpin A et al. Osteoarthritis Cartilage 2018;26(1):S40–S41.
REPORTING FROM OARSI 2018
Key clinical point: A prototype device showed a promising application as a noninvasive method to detect osteoarthritis.
Major finding: In a model that combined it with BMI and age, the device had an area under the curve of 84%, which suggested that this device might be able to improve OA detection.
Study details: Single-center study of 66 women aged 44-67 years old; 51.5% had radiographically confirmed OA of Kellgren-Lawrence grade 2 or higher.
Disclosures: Mr. Tiulpin did not have any conflicts of interest to disclose.
Source: Tiulpin A et al. Osteoarthritis Cartilage. 2018;26(1):S40–S41.
