KOALA from ImageBiopsy Lab

Ambra Health and Image Biopsy Lab Solution Directory

KOALA (Knee OA Labeling Assistant) is a radiological fully-automated image processing software device intended to aid medical professionals in the measurement of standard joint space width parameters, as well as perform an assessment of OARSI grades for sclerosis, joint space narrowing and osteophytes, and an OA classification of the joint according to Kellgren & Lawrence of standing, fixed-flexion radiographs of the knee.

It should not be used in lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis. The system is to be used by trained professionals including, but not limited to, radiologists, orthopedics, physicians and medical technicians.

KOALA from ImageBiopsy Lab

Product Features:

Consistent Readings:
  • Inter-rater variability has been a challenge for OA severity classification such as KL and OARSI grades
  • A reader study shows that physicians reading radiographs for KL and OARSI grades show significantly improved agreement rates when aided by KOALA’s report. Improvements in agreement rates range from 37% for Joint Space Narrowing OARSI grades to 101% for KL grades
More Accurate Readings:
  • A reader study shows that the physicians’ rate of false positives for KL and OARSI grades decreases greatly when compared to the gold standard: False positive rates decrease by 29% for the detection of any knee joint abnormality, 43% for the detection of osteophytes,  and by 66% for the detection of severe sclerosis.
Automated Reporting:
  • KOALA provides a standardized report that can be produced automatically as the radiographs enter the PACS system. This supports the physician’s workflow by saving time and ensures an auditable record of the patient’s exams

Clinically Relevant OA Inclusion/Exclusion Criteria

  • KOALA provides indicators for presence/absence of the relevant OA features: Joint space narrowing, Osteophyptes and Sclerosis, supportive for the stratification of cohorts for clinical studies.


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IB Lab’s mission is to improve the diagnostic experience of patients and go beyond the current standard in medical imaging. Often diagnoses are too late, subjective and inconsistent due to time pressure. This requires an immediate solution. IB Lab uses state-of-the-art technology through artificial intelligence to solve these problems efficiently.

The knee joint is the largest joint in the body and has a complex structure. Filtering out relevant diagnostic information is particularly time-consuming. KOALA-supported diagnostic reporting increases the agreement rate among physicians of up to 70% and on average by 23%. Up to 2-fold improvements in the specificity of readers aided by KOALA decrease the rate at which healthy patients are wrongly diagnosed with OA. Thus, reducing the subjectivity by KOALA decreases deviations in disease assessment. As a result, KOALA supports objective and standardized monitoring of radiological parameters during the course of a disease.