Kinect Used to Better Estimate Body Size and CT Radiation Dose

Kinect Used to Better Estimate Body Size and CT Radiation Dose

Kinect attaches to the Xbox 360 gaming console and enables users to control game play using a camera and a microphone. In essence, it is a combination RGB camera/infrared depth sensor device.

Imaging informatics researchers at the Hospital of the University of Pennsylvania are using Kinect to help accurately estimate whole-body volume. They plan to use this information to provide CT dose estimates that better reflect a patient’s body habitus and to better position patients within CT scanner bores. Dr. Tessa Cook, PhD, a radiology fellow, presented the work undertaken to date and what she and her colleagues have learned from their experiments.

There is growing interest in being able to accurately and routinely monitor patient exposure to ionizing radiation. Existing methods of estimating whole-body effective dose provide straightforward, practical ways to estimate radiation exposure to a patient, but they often do not incorporate patient size.

For example, research has already shown that dose-length product (DLP) can underestimate radiation dose for small patients, especially children, and overestimate dose for larger adults.

“There are many potential estimates of a patient’s size, including height, weight, body mass index, and the effective diameter of the anatomy being imaged,” Cook explained. “But none of these measures effectively captures the size of the region of anatomy being imaged. We wanted to identify a way to do this rapidly, efficiently, and easily.”

The Kinect controller does this when an individual stands in front of the camera for several seconds. Software developed by Radimetrics registers a depth map and computes a skeletonization of the person, and the data are used to estimate the volume of the individual. Volume is calculated in real-time while the individual stands approximately 5 ft to 6 ft (2.5 m) from the camera.

Software developed by Radimetrics registers a depth map and computes a skeletonization of the person, and the data are used to estimate the volume of the individual. Image courtesy of Dr. Gregory Couch, Radimetrics.

The hospital’s initial test of the Kinect-driven system included five adults — two men and three women — ranging in age from 35 to 45. The volunteers were imaged with their hands upright, crossed, and by the sides of their body to estimate whole-body volume.

The researchers discovered that using two cameras positioned at a 90° angle to one another provided more-accurate information. They also experimented with patients standing in frontal and lateral positions.

The researchers hypothesized that the density of each individual would be close to 1,000 kg/m3, or the density of water, as the human body is primarily composed of water. They determined that the average density for the volunteers was 995.2 kg/m3 when they positioned their arms by their sides, 805.1 kg/m3 when they extended their arms upward, and 1,136.8 kg/m3 when they crossed their arms over their chests.

“Whole-body volume estimates can provide information about the thickness of a patient, which is relevant not only to how much dose the patient receives during an exam, but also how much is necessary to produce diagnostic-quality images,” Cook said. “While the volume generated by our system is of a patient’s entire body, it can be matched to the region of a patient being imaged in order to provide a regional size estimate and, ultimately, more accurate radiation dose estimates corrected to size.”

More work is needed to investigate the differences introduced by patient height and age, as well as the clothing worn. Baggy clothes and hospital gowns cause differences in measurements. The next step is to image 40 or 50 volunteers and to begin to study pediatric patients. The researchers also intend to determine how volume measurements are affected by patients lying prone on exam tables.

Currently, data are not captured, which needs to occur for the information to be utilized. “In another year, we expect to have a lot more to report,” Cook concluded.

Hypothesis:

We hypothesize that the depth information provided by the Microsoft Kinect will provide an accurate estimate of whole-body volume. We assume that the density of the body estimated from this volume calculation will be close to 1000 kg/m3, which is the density of water. We also hypothesize that arm position will cause variations in the volume estimation, specifically, that volume estimates with the arms crossed over the chest will differ from volume estimates when the arms are by the sides or extended above the head but not overlapping with the body.

Introduction:

There is growing interest in being able to accurately and routinely monitor patients’ exposure to ionizing radiation. Historically, whole-body effective dose has been estimated by multiplying the dose-length product (DLP) by the anatomy-specific conversion factor, or k factor, derived from tissue-specific weighting factors determined by the International Commission for Radiological Protection (ICRP). While deriving effective dose from DLP provides a straightforward, practical estimate of patients’ radiation exposure, it does not reflect patient size [1]. Using Monte Carlo simulations of CT scans and subsequent calculation of organ doses, researchers have demonstrated that DLP can underestimate dose for smaller patients, including children, and overestimate dose for larger adults [2, 3]. It is critical to understand that CTDI and the associated dose indices do not represent actual patient dose [4]. This motivated the AAPM to develop correction factors for CTDIvol based on effective patient diameter [5]. Additional work has been done to normalize for inherent differences in scanner geometries and enable comparisons of dose estimates between scanners, however, these corrections still do not account for patient factors—size, gender, body habitus [6, 7]. Recent work using Monte Carlo simulations to calculate organ doses from anthropomorphic phantoms of different sizes has more clearly illustrated how much DLP can vary with patient size [8, 9]. However, computational needs render it impractical to model every patient individually, necessitating the need for standardized phantoms.

There are many potential estimates of patient size–height, weight, body mass index (BMI), effective diameter of the anatomy being imaged. However, none of these measures effectively captures the size of the region of anatomy being imaged. To address this limitation, we present and validate a novel approach to estimating patient volume using the Microsoft Kinect, a combination RGB camera-infrared depth sensor device.

Methods:

The algorithm, developed by Radimetrics Inc., registers a depth map and computes a skeletonization of an individual who appears in front of the Kinect camera-sensor. The combination of these data is used to estimate the volume of the individual. The depth map does not display or record any identifiable features of the person, and is not saved after he/she leaves the viewing frame (Figure 1). Volume is calculated in real-time while the individual remains in front of the device. The volume estimate is continuously refined and recalculated as long as the individual remains within the camera’s field of view.

Figure 1

To validate the feasibility of using this Kinect camera-sensor for estimating patient size, we compare the calculated volume of seven non-patient volunteers and compare this value to each individual’s weight. No identifiable information about the volunteers is stored; weights and volumes are recorded anonymously. The effect of position on the volume estimation is also evaluated by estimating each volunteer’s whole-body volume with the arms by their sides, extended above the head or crossed over the chest.

Results:

Weight and volume estimates for a total of seven non-patient volunteers (five adults, two children; four males, three females) were compared. The volume estimates were obtained with each individual positioned approximately 2.5 meters in front of the Kinect camera system, standing on a scale to register their weight. To test the repeatability of the volume estimates, multiple depth images were analyzed for each individual. Repeated volume estimates were noted to be within one significant digit. Figure 2 demonstrates the depth map produced by the system for six of the volunteers – two adults and four children. In this figure, the volunteers are all standing with their arms to the sides. Figure 3 demonstrates the additional arm positions that are evaluated: arms extended upward (left) and arms crossed over the body (right).

Figure 2

Figure 3

Figure 4 compares the volume estimates computed for the three different arm configurations. Not surprisingly, there is a clear difference between the volume estimates in the two children (volunteers 2 and 3) and the remaining adults. Volume is observed to increase when the arms are extended over the head and decrease when they are crossed in front of the body. This trend is also noted in the density estimates.

Figure 4

Density is calculated by dividing each individual’s weight by his or her volume. We hypothesized that the density of each individual would be close to 1000 kg/m3, or the density of water, as the human body is primarily composed of water. The average density for the five adult volunteers is 995.2 kg/m3 with the arms by the sides, 805.1 kg/m3 with the arms extended upwards and 1136.8 kg/m3 with the arms crossed over the chest. When the arms are extended overhead, the body appears to occupy a larger volume but a higher proportion of that volume appears to be composed of air, thus resulting in a lower density estimate. Similarly, when the arms are crossed over the body, the body occupies a lower volume but appears to be composed not of air, thus increasing the estimates. Some of this variation may arise from the overall angulation of the body that can occur out of the coronal plane when the arms are positioned differently. Nevertheless, this variation with position motivates a more robust volume estimation that can account for these positional differences.

The density estimates for the two children were nearly 50% of that of the adult volunteers for each analyzed position. This was not an expected result and may be secondary to a true density difference between adults and children or the need for more precise centering in the longitudinal (head-to-toe) direction of shorter individuals in front of the Kinect camera.

Source : http://www.siim2012.org/abstract_SSA_Cook.shtml

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