We present an algorithm for automatic anatomical measurements in tomographic datasets of the knee. The algorithm uses a set of atlases, each consisting of a knee image, surface segmentations of the bones, and locations of landmarks required by the anatomical metrics. A multistage volume-to-volume and surface-to-volume registration is performed to transfer the landmarks from the atlases to the target volume. Manual segmentation of the target volume is not required in this approach. Metrics were computed from the transferred landmarks of a best-matching atlas member (different for each bone), identified based on a mutual information criterion. Leave-one-out validation of the algorithm was performed on 24 scans of the knee obtained using extremity cone-beam computed tomography. Intraclass correlation (ICC) between the algorithm and the expert who generated atlas landmarks was above 0.95 for all metrics. This compares favorably to inter-reader ICC, which varied from 0.19 to 0.95, depending on the metric. Absolute agreement with the expert was also good, with median errors below 0.25 deg for measurements of tibial slope and static alignment, and below 0.2 mm for tibial tuberosity-trochlear groove distance and medial tibial depth. The automatic approach is anticipated to improve measurement workflow and mitigate the effects of operator experience and training on reliability of the metrics.
Despite the use of protective equipment, burns are a significant source of battlefield injury particularly for operators of military vehicles. Burn severity is classified by the depth of heat penetration which is dependent on skin thickness. Current ASTM values for skin thickness used in burn injury models are based on forearm estimates. However, variations in skin thickness with body location and posture may be critical to accurately estimate burn injury and develop thermal protective equipment. This study used ultrasound to quantify epidermis and dermis skin layer thicknesses at various locations and postures on a human body. Superficial ultrasound images of seventeen male military personnel were obtained using a 22MHz linear probe (LOGIQe, GE). Three images were taken at twelve different locations. Hand locations were scanned in a neutral posture as well as a clenched-fist posture akin to grasping a steering wheel while operating a military vehicle. Measurements of the epidermis and dermis were obtained at each location and mean results were taken. Measured values were compared to the ASTM standard using a one sample t-test. In general, measured epidermis and dermis layer thickness was significantly larger compared to the current standard. The effect of hand posture was determined using a two sample t-test. Dermis values significantly decreased with the clenched fist posture while the epidermis remained unchanged between the two postures. Obtaining in-vivo skin thicknesses across the body will allow for more accurate predictions of burn injury and more efficient thermal protective equipment.
Purpose: Anatomical metrics of the tibiofemoral joint support assessment of joint stability and surgical planning. We propose an automated, atlas-based algorithm to streamline the measurements in 3D images of the joint and reduce userdependence of the metrics arising from manual identification of the anatomical landmarks.
Methods: The method is initialized with coarse registrations of a set of atlas images to the fixed input image. The initial registrations are then refined separately for the tibia and femur and the best matching atlas is selected. Finally, the anatomical landmarks of the best matching atlas are transformed onto the input image by deforming a surface model of the atlas to fit the shape of the tibial plateau in the input image (a mesh-to-volume registration). We apply the method to weight-bearing volumetric images of the knee obtained from 23 subjects using an extremity cone-beam CT system. Results of the automated algorithm were compared to an expert radiologist for measurements of Static Alignment (SA), Medial Tibial Slope (MTS) and Lateral Tibial Slope (LTS).
Results: Intra-reader variability as high as ~10% for LTS and 7% for MTS (ratio of standard deviation to the mean in repeated measurements) was found for expert radiologist, illustrating the potential benefits of an automated approach in improving the precision of the metrics. The proposed method achieved excellent registration of the atlas mesh to the input volumes. The resulting automated measurements yielded high correlations with expert radiologist, as indicated by correlation coefficients of 0.72 for MTS, 0.8 for LTS, and 0.89 for SA.
Conclusions: The automated method for measurement of anatomical metrics of the tibiofemoral joint achieves high correlation with expert radiologist without the need for time consuming and error prone manual selection of landmarks.
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