IB Lab LAMA uses deep learning technology for automated and precise measuring of leg geometry to evaluate lower limb deformities. It aids in the detection of genu varum/valgum by measuring mechanical axis deviation (MAD) and detection of leg length discrepancy by comparing right and left legs on bilateral images. Detailed analysis of mechanical and anatomical angles according to Paley allows informed decision making on next steps in treating the patient. IB Lab LAMA’s measurements of HKA, JLCA and MAD are precise to within 0.3°, 0.8° and 1.1 mm and leg length discrepancy is accurate to 0.2 cm of expert readers augmenting reading results especially of non-experts. Reading time is brought down from 8 minutes to under 60 seconds needed for calculation 1.
IB Lab LAMA highlights relevant clinical findings by applying latest international medical standards to enable timely and accurate decision making. The findings are summarized in a visual report, attached to the original x-ray image and saved automatically in the PACS system. The AI facilitates monitoring of disease progression by facilitating comparison of radiographic disease parameters over time.
Radiological findings and measurements including: genu varum, genu valgum, lower extremity length discrepancy, mechanical angles according to Paley, mechanical axis deviation (MAD), hip knee ankle angle, joint line convergence angle, leg length, femur length, tibia lengthNEW: support of implants and automated calibration ball detection.
- Quicker pre-selection by instantly triaging normal and abnormal cases
- Increases workflow efficiency by saving reading and reporting time
- Reduces the risk of inter-rater variability for evaluating long leg radiographs in a standardized manner
IB Lab LAMA is a radiological fully-automated image processing software device of either computed (CR) or directly digital (DX) images intended to aid medical professionals in the measurement of leg geometry. IB Lab LAMA aids in the detection of knee alignment deformities by providing the following measurements: mechanical lateral proximal femur angle (mLPFA), mechanical lateral distal femur angle (mLDFA), mechanical medial proximal tibia angle (mMPTA), mechanical lateral distal tibia angle (mLDTA), mechanical axis deviation (MAD), hip-knee-ankle angle (HKA), anatomical-mechanical axis angle (AMA) on standing AP radiographs of the leg. IB Lab LAMA aids in the detection of leg length discrepancy by providing the following measurements: femur, tibia and full leg length as well as the difference between right and left legs on bilateral images.
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 medical professionals including, but not limited to, orthopedists and radiologists.
Training and Validation
Deep learning algorithms trained on over 20,000 individual knee, hip and full leg radiographs. From consensus graded data set provided by a large European orthopedic hospital. AI based on Deep Learning to automatically recognize and localize anatomically relevant landmarks on the hip, knee and ankle.
- Gary A Knutson: Anatomic and functional leg-length inequality: A review and recommendation for clinical decision-making. Part I, anatomic leg-length inequality: prevalence, magnitude, effects and clinical significance, Chiropractic & Osteopathy, 2005.
- G. McDaniel, K.L. Mitchell, C. Charles, V.B. Kraus: A comparison of five approaches to measurement of anatomic knee alignment from radiographs, November 16, 2009.
- James M Hartford, Michael J Bellino: The learning curve for the direct anterior approach for total hip arthroplasty: a single surgeon’s first 500 cases, September 19, 2017.
- World Health Organization: Increasing complexity of medical technology and consequences for training and outcome of care, August 2010.
- IB Lab LAMA Clinical Validation study
- IB Lab US Market Survey 2020