CORONARY CALCIUM MEASUREMENT
TECHNICAL FIELD
The present Invention relates generally to medical testing to assist patient diagnosis and, in particular, to performing coronary calcium measurement using contrast enhanced computerised tomography.
BACKGROUND
Medical practitioners have available a range of tests, equipments and processes that can assist in patient assessment and diagnosis. In coronary care, the most informative and traditional test is commonly known as the angiogram. Here, a contrast dye is injected into the bloodstream and X-ray images of the heart and surrounding vascular system are captured to permit practitioners to identify abnormalities in the heart muscle, valves and coronary arteries.
The computed tomography (CT) scan is a medical imaging procedure that uses X- rays and computing technology to create cross-section images of the body. CT can image every type of body structure at once including bone, blood vessels and soft tissue. The CT scan may also be referred to by its older name of computer assisted tomography or 'CAT' scan. CT is used in coronary care generally in two ways. The first is contrast enhanced CT coronary angiography which is akin to the angiogram discussed above, but where the traditional (2-dimensional) X-ray is replaced by what is effectively a (3-dimensional) CT scan. The second use involves a standard CT scan of the heart to identify calcium deposits. This scan does not involve the injection of iodinated contrast, and is generally acquired or reconstructed at a coarser resolution.
Coronary calcium measurement from non-contrast (standard) CT is most frequently presented using the Agatston score but may also be represented as calcium volume or calcium mass and is a powerful predictor of future cardiovascular risk and which provides information supplemental to traditional Framingham risk assessment. While the radiation dose of contrast enhanced cardiac CT has diminished rapidly in recent years due to ongoing technological developments of CT machines, the radiation dose of calcium score evaluation is largely fixed due to protocol constraints necessary to adequately identify coronary calcium. In some cases, the radiation dose used in calcium score scans now equals or exceeds the radiation dose of contrast enhanced CT coronary angiography.
Thus, it is common for coronary patients to be subjected to both calcium CT measurement and contrast enhanced CT angiogram in order to provide practitioners will all the relevant information necessary for diagnosis. This necessarily exposes the patient to two significant doses of radiation. This problem is exacerbated for patients with chronic conditions requiring repeated assessment over time. Previous attempts to measure coronary calcium from contrast enhanced coronary CT have either been unable to separate intra- coronary contrast from intra-mural calcium, or have been unable to adequately measure lower density coronary calcium that is often present in individuals with lower coronary calcium scores. One failed attempt stated achieving a dual-test would be difficult with standard equipments.
SUMMARY
Disclosed is a novel method for the estimation of calcium scores from contrast- enhanced CT, without the need for additional radiation incurred by supplemental non-contrast CT scanning. Such method may be performed using existing equipments and through use of existing software.
According to one aspect of the present disclosure, there is provided a method of coronary calcium measurement of a patient, the method comprising:
performing a contrast-enhanced coronary computed tomography (CT) scan of the patient and recording results of the scan; and
processing the recorded results for calcium measurement by:
segmenting the coronary arteries from the recorded results;
extracting the coronary wall from the contrast filled coronary lumen;
applying a threshold to voxels within the extracted coronary walls; and applying at least one conversion factor to convert the voxels obtained to at least one of an Agatston and a calcium volume score.
The processing desirably includes image processing of CT images of the recorded results. The processing may also include manual selection of features within CT images of the recorded results. The processing may include computer processing of the images to select a volume of interest associated with calcium fragments of the coronary wall.
Preferably, the calcium associated voxel brightness threshold is in the range 240 - 560 HU. More typically, the threshold is in the range 240 - 440 HU. Most preferably the threshold is about 320 HU.
Typically, the conversion factor is contingent upon the threshold. Usually the conversion factor is substantially linearly related to the threshold. Further, the conversion factor is generally dependent upon the type of CT machine used for the scan and the threshold selected for the patient.
Other aspects are also disclosed.
BRIEF DESCRIPTION OF THE DRAWINGS
At least one embodiment of the present invention will now be described with reference to the drawings, in which:
Figs. 1A and 1 B collectively represent a CT imaging system used for both calcium score measurement and contrast enhanced CT angiography;
Fig. 2 is a flowchart of a method for coronary CT measurement for both angiography and calcium measurement;
Fig. 3 is an example of automated (A) and manual (B) calcium segmentation of a CT image resulting in a volume of interest (VOI) consisting of the coronary wall containing calcium fragments (C,D);
Fig. 4 is a flowchart of step 220 of Fig. 2;;
Figs. 5A and 5B are plots of exemplary conversion factors for Philips and Toshiba CT machines based on corresponding variable thresholds used to generate an Agatston calcium scores;
Fig. 6 is a plot of a further exemplary Toshiba conversion factor to generate a calcium volume score; and
Fig. 7 show a statistical analysis of test results from the validation study demonstrating the correlation between the method described and traditional means of measurement.
DETAILED DESCRIPTION INCLUDING BEST MODE
Testing System Architecture
Figs. 1A and 1 B depict a general-purpose computer system 100 and associated CT apparatus 190, upon which the various arrangements described can be practiced.
As seen in Fig. 1A, the computer system 100 includes: a computer module 101 ; input devices such as a keyboard 102, a mouse pointer device 103, a scanner 126, a camera 127, and a microphone 180; and output devices including a printer 115, a display device 114 and loudspeakers 1 17. An external Modulator-Demodulator (Modem) transceiver device 116 may be used by the computer module 101 for communicating to and from a communications network 120 via a connection 121. The communications network 120 may be a wide-area network (WAN), such as the Internet, a cellular telecommunications network, a private WAN, or a local area network (LAN). Where the connection 121 is a telephone line, the modem 116 may be a traditional "dial-up" modem. Alternatively, where the connection 121 is a high capacity (e.g., cable) connection, the modem 1 16 may be a broadband modem. A wireless modem may also be used for wireless connection to the communications network 120.
The computer module 101 typically includes at least one processor unit 105, and a memory unit 106. For example, the memory unit 106 may have semiconductor random access memory (RAM) and semiconductor read only memory (ROM). The computer module 101 also includes an number of input/output (I/O) interfaces including: an audio-video interface 107 that couples to the video display 114, loudspeakers 117 and microphone 180; an I/O interface 113 that couples to the keyboard 102, mouse 103, scanner 126, camera 127 and optionally a joystick or other human interface device (not illustrated); and an interface 108 for the external modem 116 and printer 115. In some implementations, the modem 116 may be incorporated within the computer module 101 , for example within the interface 108. The computer module 101 also has a local interface 111 , which permits coupling of the computer system 100 via a connection 123 to the CT apparatus 190. The interface 108 and 113 may comprise an Ethernet™ circuit card, a Bluetooth™ wireless arrangement or an IEEE 802.11 wireless arrangement; however, numerous other types of interfaces may be practiced for the interface 108.
The I/O interfaces 108 and 113 may afford either or both of serial and parallel connectivity, the former typically being implemented according to the Universal Serial Bus (USB) standards and having corresponding USB connectors (not illustrated). Storage devices 109 are provided and typically include a hard disk drive (HDD) 110. Other storage devices such as a floppy disk drive and a magnetic tape drive (not illustrated) may also be used. An optical disk drive 112 is typically provided to act as a non-volatile source of data. Portable memory devices, such optical disks (e.g., CD-ROM, DVD, Blu-ray Disc™), USB- RAM, portable, external hard drives, and floppy disks, for example, may be used as appropriate sources of data to the system 100.
The components 105 to 113 of the computer module 101 typically communicate via an interconnected bus 104 and in a manner that results in a conventional mode of operation of the computer system 100 known to those in the relevant art. For example, the processor 105 is coupled to the system bus 104 using a connection 118. Likewise, the memory 106 and optical disk drive 112 are coupled to the system bus 104 by connections 119. Examples of computers on which the described arrangements can be practised include IBM-PC's and compatibles, Sun Sparcstations, Apple Mac or a like computer systems.
The methods of coronary calcium measurement may be implemented using the computer system 100 wherein the processes to be described with reference to Figs. 2 to 4, may be implemented as one or more software application programs 133 executable within the computer system 100. In particular, the steps of the method of coronary calcium measurement are effected by instructions 131 (see Fig. 1 B) in the software 133 that are carried out within the computer system 100. The software instructions 131 may be formed as one or more code modules, each for performing one or more particular tasks. The software may also be divided into two separate parts, in which a first part and the corresponding code modules performs the coronary calcium measurement methods and a second part and the corresponding code modules manage a user interface between the first part and the user.
The software may be stored in a computer readable medium, including the storage devices described below, for example. The software is loaded into the computer system 100 from the computer readable medium, and then executed by the computer system 100. The software 133 is typically stored in the HDD 110 or the memory 106. The software is loaded into the computer system 100 from a computer readable medium, and executed by the computer system 100. Thus, for example, the software 133 may be stored on an optically readable disk storage medium (e.g., CD-ROM) 125 that is read by the optical disk drive 1 12. A computer readable medium having such software or computer program recorded on the computer readable medium is a computer program product. The use of the computer program product in the computer system 100 preferably effects an advantageous apparatus for coronary calcium measurement.
In some instances, the application programs 133 may be supplied to the user encoded on one or more CD-ROMs 125 and read via the corresponding drive 112, or alternatively may be read by the user from the networks 120 or 122. Still further, the software can also be loaded into the computer system 100 from other computer readable media. Computer readable storage media refers to any non-transitory tangible storage medium that provides recorded instructions and/or data to the computer system 100 for execution and/or processing. Examples of such storage media include floppy disks, magnetic tape, CD-ROM, DVD, Blu-ray Disc, a hard disk drive, a ROM or integrated circuit, USB memory, a magneto- optical disk, or a computer readable card such as a PCMCIA card and the like, whether or not such devices are internal or external of the computer module 101. Examples of transitory or non-tangible computer readable transmission media that may also participate in the provision of software, application programs, instructions and/or data to the computer module 101 include radio or infra-red transmission channels as well as a network connection to another computer or networked device, and the Internet or Intranets including e-mail transmissions and information recorded on Websites and the like.
The second part of the application programs 133 and the corresponding code modules mentioned above may be executed to implement one or more graphical user interfaces (GUIs) to be rendered or otherwise represented upon the display 1 14. Through manipulation of typically the keyboard 102 and the mouse 103, a user of the computer system 100 and the application may manipulate the interface in a functionally adaptable manner to provide controlling commands and/or input to the applications associated with the GUI(s). Other forms of functionally adaptable user interfaces may also be implemented, such as an audio interface utilizing speech prompts output via the loudspeakers 1 17 and user voice commands input via the microphone 180.
Fig. 1 B is a detailed schematic block diagram of the processor 105 and a
"memory" 134. The memory 134 represents a logical aggregation of all the memory modules (including the HDD 109 and semiconductor memory 106) that can be accessed by the computer module 101 in Fig. 1A.
When the computer module 101 is initially powered up( a power-on self-test (POST) program 150 executes. The POST program 150 is typically stored in a ROM 149 of the semiconductor memory 106 of Fig. 1A. A hardware device such as the ROM 149 storing software is sometimes referred to as firmware. The POST program 150 examines hardware within the computer module 101 to ensure proper functioning and typically checks the processor 105, the memory 134 (109, 106), and a basic input-output systems software (BIOS) module 151 , also typically stored in the ROM 149, for correct operation. Once the POST program 150 has run successfully, the BIOS 151 activates the hard disk drive 1 10 of Fig. 1A. Activation of the hard disk drive 110 causes a bootstrap loader program 152 that is resident on the hard disk drive 1 10 to execute via the processor 105. This loads an operating system 153 into the RAM memory 106, upon which the operating system 153 commences operation. The operating system 153 is a system level application, executable by the processor 105, to fulfil various high level functions, including processor management, memory management, device management, storage management, software application interface, and generic user interface. The operating system 153 manages the memory 134 (109, 106) to ensure that each process or application running on the computer module 101 has sufficient memory in which to execute without colliding with memory allocated to another process. Furthermore, the different types of memory available in the system 100 of Fig. 1A must be used properly so that each process can run effectively. Accordingly, the aggregated memory 134 is not intended to illustrate how particular segments of memory are allocated (unless otherwise stated), but rather to provide a general view of the memory accessible by the computer system 100 and how such is used.
As shown in Fig. 18, the processor 105 includes a number of functional modules including a control unit 139, an arithmetic logic unit (ALU) 140, and a local or internal memory 148, sometimes called a cache memory. The cache memory 148 typically include a number of storage registers 144 - 146 in a register section. One or more internal busses 141 functionally interconnect these functional modules. The processor 105 typically also has one or more interfaces 142 for communicating with external devices via the system bus 104, using a connection 118. The memory 134 is coupled to the bus 104 using a connection 119.
The application program 133 includes a sequence of instructions 131 that may include conditional branch and loop instructions. The program 133 may also include data 132 which is used in execution of the program 133. The instructions 131 and the data 132 are stored in memory locations 128, 129, 130 and 135, 136, 137, respectively. Depending upon the relative size of the instructions 131 and the memory locations 128-130, a particular instruction may be stored in a single memory location as depicted by the instruction shown in the memory location 130. Alternately, an instruction may be segmented into a number of parts each of which is stored in a separate memory location, as depicted by the instruction segments shown in the memory locations 128 and 129.
In general, the processor 105 is given a set of instructions which are executed therein.
The processor 1105 waits for a subsequent input, to which the processor 105 reacts to by executing another set of instructions. Each input may be provided from one or more of a number of sources, including data generated by one or more of the input devices 102, 103, data received from an external source across one of the networks 120, 102, data retrieved from one of the storage devices 106, 109 or data retrieved from a storage medium 125 inserted into the corresponding reader 1 12, all depicted in Fig. 1A. The execution of a set of the instructions may in some cases result in output of data. Execution may also involve storing data or variables to the memory 134. The disclosed coronary calcium measurement arrangements use input variables 154, which are stored in the memory 134 in corresponding memory locations 155, 156, 157. The calcium measurement arrangements produce output variables 161 , which are stored in the memory 134 in corresponding memory locations 162, 163, 164. Intermediate variables 158 may be stored in memory locations 159, 160, 166 and 167.
Referring to the processor 105 of Fig. 1 B, the registers 144, 145, 146, the arithmetic logic unit (ALU) 140, and the control unit 39 work together to perform sequences of micro- operations needed to perform "fetch, decode, and execute" cycles for every instruction in the instruction set making up the program 133. Each fetch, decode, and execute cycle comprises:
(a) a fetch operation, which fetches or reads an instruction 131 from a memory location 128, 129, 130;
(b) a decode operation in which the control unit 139 determines which instruction has been fetched; and
(c) an execute operation in which the control unit 139 and/or the ALU 140 execute the instruction.
Thereafter, a further fetch, decode, and execute cycle for the next instruction may be executed. Similarly, a store cycle may be performed by which the control unit 139 stores or writes a value to a memory location 132.
Each step or sub-process in the processes of Figs. 2 to 4 is associated with one or more segments of the program 133 and is performed by the register section 144, 145, 147, the ALU 140, and the control unit 139 in the processor 105 working together to perform the fetch, decode, and execute cycles for every instruction in the instruction set for the noted segments of the program 133.
Fig. 2 is a schematic flow diagram of a method 200 of coronary CT testing by which the systems shown in Fig. 1 may be operated. In an initial step 202, the computer apparatus 100 and CT apparatus 190 of Fig. 1A are operated to perform a contrast enhanced coronary CT of a patient, this resulting in the output of coronary CT data which is stored in the computer 100, typically in the HDD 1 10 in step 204. The cardiac CT scan is acquired at higher resolution than traditional calcium scores, which are have coarse pixels. The present inventor has found that a slice thickness of less than 2.5mm is desired.
In step 206 where desired the coronary CT data may be processed in a traditional fashion by the computer 100 for angiography evaluation and step 208 stores the consequential angiography images and associated data. Where desired, step 210 provides for the display of the images and/or data on the video display 114 for diagnostic evaluation.
The stored CT data is processed at step 220 by the computer 100 for coronary calcium measurement. The processing of step 220 involves the setting of appropriate thresholds, amongst other steps to be described, and results in the calcium measurement being stored in the HDD 110 in step 222. At step 224, the calcium measurement may be retrieved from the HDD 110 and displayed on the display 1 14 or printed via the printer 115 for diagnostic evaluation.
Agatston calcium score and Calcium Volume measurement
According to steps 202 and 204, CT coronary angiographic data is acquired and stored as for any routine clinical examination. This is typically done after the installation of intravenous iodinated contrast. Standard processing of the resultant dataset typically results in the reconstruction of a series of axial slices with voxels of greater resolution (<1 mm3) than standard non-contrast calcium score calculation protocols. This information may be used for clinical purposes including traditional detection of coronary artery stenoses. As described below, this data may also be used to determine the calcium score, calcium volume or calcium mass without the need for a supplementary scan.
Fig. 4 which shows detail of the processing of step 220 for coronary calcium measurement. In a first step 402 the series of axial slices from steps 202 and 204 is combined to form a three dimensional volumetric data set. From the volumetric data set, the coronary arteries are then segmented or otherwise identified. The contrast filled coronary lumen is separately identified and the calcium containing coronary wall is separately identified. Several computer programs and algorithms have been created that allow the identification or segmentation of the coronary arteries from a three dimensional data set containing the heart, great vessels and other contents of a thoracic volume. The segmentation and identification may either be achieved as a manual process, or more usually as a semi-automated or automated method using the known programs and algorithms. One example of such a method involves the manual placement of a 'seed' within a coronary artery which is then algorithmically propagated to include the entire volume of the coronary lumen based on voxel density and proximity to the seed or the initially propagated lumen. Similarly, software methods and algorithms exist to allow the identification of the coronary artery wall surrounding the contrast filled lumen. Such software tools typically allow the selection of a volume of interest including the coronary wall calcium fragments and excluding the contrast filled lumen. Such analysis may also be performed with manual selection and adjustment. An example of the use of one such system (SurePlaque™) is shown in Fig. 3.
In Fig. 3, A depicts that automated calcium identification is successful in most of the artery, including area 1 , with the calcium lying between blue (luminal border) and brown (outer coronary surface). In areas 2 and 3 small calcium deposits have been included within the artery lumen. In Fig. 3, B depicts the lumen borders are manually adjusted to exclude intramural calcium resulting in the contours shown in C. Also, in Fig. 3, D depicts a final volumetric assessment of all calcium, shown as yellow, can be made.
All such segmentation and identification necessarily involve the analysis of a volumetric data set, i.e. the inclusion of any given voxel within an a coronary intramural region of interest is contingent on the surrounding voxels above and below the slice containing the voxel. It should be noted that the standard and usual method of measuring coronary calcium which utilizes analysis performed within the axial plane cannot adequately separate coronary lumen contents from the calcium containing coronary wall.
Step 404 then extracts the coronary wall from the contrast filled coronary lumen. This process may use edge detection, density thresholds, propagation from initial seeds, etc. Such cannot be adequately performed by simply analysing axial slices as analysis within the axial plane, as such does not enable adequate delineation of the coronary lumen and coronary wall, particularly in the presence of coronary calcium and software tools require an element of three dimensional analysis, typically in the direction of coronary flow or coaxial to coronary flow. Usually a 'centreline' through the coronary artery is created from which subsequent analysis is dependent.
The final result of step 404 is a volume of interest (VOI) recorded in the computer 101 of voxels representing the coronary wall, but largely excluding the contrast containing lumen. This volume of interest contains the calcium fragments which lie within the coronary wall and which are to be measured, but excludes the contrast filled coronary lumen. The volume of voxel elements within the VOI relating to a certain brightness density (or Hounsfield unit - "HU") associated with calcium may then be acquired without the risk of interference from intraluminal contrast. The VOI may also be restricted by manual or automatic means to only those coronary arteries or coronary artery segments than contain calcium fragments.
This is not in itself sufficient to allow quantification of coronary calcium, however. The use of the traditional lower calcium detection threshold of 130 HU when applied at a smaller voxel size such is required for accurate volumetric assessment of the contrast enhanced CT data leads to spurious calcium measurement. The present inventor found that at an imaged voxel size of approximately 0.5mm3 non-calcified mural elements including fibrotic and collagenous deposits often occupied the Hounsfield range between 130 HU and approximately 200 HU, whereas true calcified plaques generally greatly exceed 300 HU. Furthermore, imperfect coronary lumen segmentation, partial voluming effects and streak artifact cause substantial interference at standard calcium scoring thresholds. Conversely, if a very high threshold of 600 HU or greater is used, areas of the coronary artery that are only lightly calcified may be excluded from further analysis providing a spuriously low calcium score reading. Thus as next step 406, a threshold of between 240 - 560 HU is applied to the VOI to calculate the volume of voxel elements above this selected threshold and which represent calcified material. This threshold must be greater than the lower threshold used for traditional calcium scoring (130 HU), but not so high as to ignore non-dense calcium (<600 HU). The range 240 to 560 HU has been studied and shown to be effective, although the best thresholds lie near 320 HU, and generally in the range 240 - 440 HU. The result will be a coronary wall voxel volume consisting of those voxels greater than the selected threshold.
Due to partial voluming and geometric factors, small voxel, higher threshold calcium elements measured within the VOI by step 406 do not correspond exactly to the large pixel, traditional calcium measurement which includes lower density structures. Therefore, step 408 is then performed to convert the voxel volume measured in step 2 into a calcium score, calcium volume, or calcium mass equivalent to traditional quantifications techniques. In step 408, the calcium volume above a selected threshold is multiplied by a corresponding conversion factor.
The conversion factor used is contingent on the threshold selected. The relationship between the required conversion factor and threshold can be represented as a function, which is substantially linear between 240 and 560 HU. A different conversion function is used depending on whether the calcium score, volume or mass is to be measured. The conversion function varies slightly between CT machine models as it is influenced by a small extent by voxel size, X-ray energy and software reconstruction and kernel parameters. Although a universal conversion function may be used, for the most accurate clinical measurement a conversion function may be obtained for each CT model. The conversion factor is contingent on the threshold selected between 130 and 600 HU. The relationship between the conversion factor and threshold selected is generally linear or near linear across the recommended Hounsfield ranges. Higher thresholds require higher conversion factor. The conversion function (being the relationship between conversion factor and threshold) is fixed for any given CT apparatus, assuming that the voxel size used for imaging is maintained the same.
For the derivation of one such conversion function, 100 calcium score and contrast enhanced coronary CT pairs were analysed by the present inventor to derive a conversion function illustrated in Fig. 5B, for a 320 detector row Aquilion One CT scanner manufactured by Toshiba Medical Systems, Tokyo, Japan. When the conversion function and described technique was evaluated in 110 sample patients using further calcium score and contrast enhanced CT pairs, the conversion function and technique demonstrated equivalent accuracy to traditional methods of calcium measurement which otherwise necessitate a second, non- contrast CT scan (Fig. 7). In Fig. 5B, the conversion factor to generate the Agatston calcium score may be interpreted as the slope of a line of best fit between the test results, and may be approximated by the equation:
Toshiba conversion factor
= 1.12 x 10"2 x Hounsfield threshold - 0.41.
(for Agatston score output) For example, if a 320 HU threshold is selected, the conversion factor is about 3.2 to generate Agatston scores from a Toshiba Aquilion One machine.
A second example of a conversion function to generate the Agatston calcium score is demonstrated in Fig. 5A for a Philips 64 slice CT machine, which gives a conversion factor according to an approximate equation:
Philips conversion factor
= 9.5 x 10'3 x Hounsfield threshold.
(for Agatston score output) For example, if a 320HU threshold is selected the conversion factor is about 3
The above steps are sufficient if the entire coronary tree is included within a VOL Otherwise the above steps may be repeated for each coronary segment until each calcium containing coronary segment has been included within a VOL The sum of the converted calcium measurements within each segment VOI then represents the estimated calcium score, mass or volume of the entire coronary tree.
From a further set of tests for the Toshiba CT machine mentioned above, as illustrated in Fig. 6, the conversion function to generate a Calcium Volume Score can be approximately represented as:
Toshiba conversion factor
= 9.45 x 10"3 x Hounsfield threshold - 0.41.
(for Calcium Volume output)
For examplej if a 320HU threshold is selected the conversion factor is approximately 2.6.
Fig. 7 depicts the output of the presently described method (Y-axis) plotted against a traditional method of measuring the Agatston calcium score (X-axis). As can be seen, the correlation between the two methods is excellent, with a correlation coefficient of greater than 0.98 across the range of calcium scores, including lower Agatston score value ranges.
INDUSTRIAL APPLICABILITY
Demonstrated is a new technique to accurately measure coronary calcium from contrast enhanced cardiac CT scans which has excellent concordance with traditional calcium scoring, minimal bias and has excellent inter-observer and intra-observer reliability. The technique obviates the need for a separate calcium score scan within standard cardiac CT protocols and may allow a substantial decrease in the total patient radiation dose across standard cardiac CT protocols. The current generation of cardiac CT scanners now possess sufficient spatial resolution, low-contrast definition, scan quality and software tools to achieve the aim of allowing clear separation of contrast filled lumen and coronary vessel in the majority of cases.
The forgoing describes only a number of embodiments of the present invention and modifications may be made thereto without departing from the scope of the invention.
For example, more than one conversion factor may be used. In this regard, one factor for the volume between 240 and 400 HU, and another factor for the volume above 400 HU.