CT Bone Mineral Density Measurement With Image-Based Phantom-Free Calibration
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Solution Overview
Problem
The existing methods for determining bone mineral density (BMD) from computed tomography (CT) scans are inaccurate and require the use of physical phantoms, which are often unavailable and uncomfortable for patients, hindering precise BMD calculations.
Innovation Solution
A computer-implemented method that identifies intensities of air, fat, and a motion rod in a medical image to determine a BMD calibration factor, allowing for BMD calculation without a physical phantom by using a relationship between these elements' intensities and their equivalent values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a physical BMD calibration phantom is used during CT scanning, then measurement precision of BMD is improved, but device complexity and patient comfort are worsened
Solution Approach 1:
The patent replaces the physical calibration phantom with a virtual calibration phantom that is digitally superimposed onto the CT image. This virtual phantom contains calibration markers with known BMD values that are generated computationally rather than physically present during scanning, thereby eliminating the need for physical phantoms while maintaining calibration accuracy.
Solution Approach 2:
The patent substitutes the mechanical/physical calibration phantom system with a computational/image processing system. The calibration process is performed through software algorithms that analyze CT image intensities and apply calibration transformations, replacing the need for physical calibration objects with digital processing methods.
2Measurement precision
If a physical BMD calibration phantom is used during CT scanning, then measurement precision of BMD is improved, but ease of operation is worsened
Solution Approach 1:
The virtual calibration phantom is digitally overlaid on the CT image, making the calibration process accessible without requiring physical phantom handling. The calibration markers are generated and positioned computationally, allowing any CT scan to be calibrated without special physical equipment.
Solution Approach 2:
The system performs self-calibration by automatically identifying calibration markers within the CT image itself and using their known BMD values to establish the calibration curve. The process is automated and does not require manual intervention or special calibration procedures by the operator.
3Measurement precision
If traditional DEXA scanning is used for BMD measurement, then measurement precision is improved, but adaptability to surgical planning is worsened
Solution Approach 1:
The patent merges BMD measurement functionality directly into the CT imaging modality. By calculating BMD from CT scan data using the calibration method, the system combines structural imaging (CT) with functional measurement (BMD) in a single procedure, eliminating the need for separate DEXA scans and enabling integrated surgical planning.
Solution Approach 2:
The CT scanner is made multi-functional by enabling it to perform both anatomical imaging and BMD measurement through the calibration algorithm. The same CT images used for surgical planning are also used for BMD assessment, making the imaging modality universal for both diagnostic and measurement purposes.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and reliable BMD determination directly from CT scans, eliminating the need for physical phantoms and providing a more accessible and comfortable method for BMD calculation.
Implementation Method 1
CT scans generate medical images, usually in grayscale, representing data in Hounsfield Units (HU). Hounsfield Units measure the attenuation of X-rays as they pass through different tissues
Data Source
AI summary
A computer-implemented method for evaluating a medical image exhibiting air, fat, a bone, and a motion rod. The computer-implemented method includes automatically performing the following: identifying, from the medical image, intensities of the bone, the motion rod and at least one of: air or fat; obtaining a bone mineral density equivalent value of the motion rod and the at least one of the air or the fat; determining a bone mineral density calibration factor based on a relationship between the identified intensities and a bone mineral density equivalent values of the motion rod and the at least one of the air or the fat; and determining the bone mineral density of the bone within the medical image based on the bone mineral density calibration factor.


