WO2016022072A1

WO2016022072A1 - Method and system for automatically identifying joints within a subject's body

Info

Publication number: WO2016022072A1
Application number: PCT/SG2015/050249
Authority: WO
Inventors: York Kiat TAN; Julian THUMBOO; Weng Kit LYE; John Carson ALLEN, Jr.
Original assignee: Singapore Health Services Pte Ltd; National University Of Singapore
Priority date: 2014-08-06
Filing date: 2015-08-04
Publication date: 2016-02-11

Abstract

The present disclosure relates to a method for automatically identifying a plurality of joints within a body of a subject to monitor across a set of joint monitoring procedures. The method includes: automatically receiving a predetermined set of joint identifiers, each joint identifier corresponding to a joint within the body; associating a score with each joint identifier in the predetermined set of joint identifiers; automatically selecting from the predetermined set of joint identifiers a plurality of joint identifiers based on the scores, wherein each selected joint identifier has a score equal to or higher than each non-selected joint identifier in the predetermined set of joint identifiers; storing each of the plurality of joint identifiers and the score associated therewith in an electronic database; and presenting visual and/or audio information corresponding to the plurality of joint identifiers on an electronic device for guiding the joint monitoring procedure(s).

Description

METHOD AND SYSTEM FOR AUTOMATICALLY IDENTIFYING JOINTS WITHIN

A SUBJECT'S BODY

Technical Field

The present disclosure generally relates to a method and system for automatically identifying a plurality of joints within a body of a subject. More particularly, aspects of the present disclosure are directed to a method and system for automatically identifying a plurality of joints within the body of the subject or patient, wherein the identified plurality of joints are monitored across a joint monitoring procedure.

Background

People sometimes experience swelling and/or pain in their body joints, such as due to disease activity in the joints. One example of a joint-related disease is rheumatoid arthritis. Rheumatoid arthritis is an autoimmune disease in which the body's immune system mistakenly attacks the joints, thereby causing pain. Affected people may also experience fatigue, loss of appetite, and/or fever. Treatments for patients who are diagnosed with rheumatoid arthritis include relieving the symptoms and reducing pain in the joints. Early diagnosis and treatment of patients can lead to better disease outcome in the joints.

There are several existing methods of monitoring the joints, such as using existing radiography, magnetic resonance imaging, and ultrasound. Ultrasound methods, particularly musculoskeletal ultrasound, are increasingly used to monitor joint inflammation in rheumatoid arthritis. The use of ultrasound monitoring methods has been facilitated by standardized definitions of ultrasound pathology in inflammatory arthritis from the European League Against Rheumatism (EULAR) Outcome Measures in Rheumatology (OMERACT) ultrasound workgroup. Further, the validation of a semi-quantitative scoring system for synovitis also facilitated the use of ultrasound monitoring. Synovitis is the inflammation of the synovial membrane around synovial joints.

Ultrasound has some advantages over magnetic resonance imaging, such as good patient tolerability and ability to scan multiple joints within a short period of time. However, it is not always feasible and effective to continually scan and monitor all the joints of the body. A reduced set of joints has been used in some monitoring procedures. Various criteria have been used for reduced joint selection, such as frequency of involvement, feasibility, representativeness of joints, and/or with logistic regression models. Further, ultrasound monitoring provides the possibility of scanning fewer joints, thereby reducing the time required, and also correlates well with extended joint scanning or scanning of a large number of joints. Existing methods of using the ultrasound include using a pre-defined 7-joint count as well as 12-joint count derived using ultrasound reduction data from the frequency of inflammatory joint involvement from an extended number of joints for ultrasound monitoring and/or scanning. Another commonly used clinical method of monitoring the joints is using the DAS28 method. DAS refers to disease activity score, and 28 refers to the 28 joints of the human body that are predetermined for assessment using this method.

Monitoring using reduced joint numbers was shown to be representative of the inflammatory changes using extended ultrasound monitoring. However, because the extent and distribution of affected joints differs between individuals, such joint selection methods do not ensure selection of the most affected joints or the greatest number of affected joints per individual for ultrasound monitoring.

Therefore, in order to address or alleviate at least one of the aforementioned problems and/or disadvantages, there is a need to provide a method and system for automatically identifying a plurality of joints within a subject's body, in which there are at least some improved features over the prior art.

Summary

According to a first aspect of the present disclosure, there is a method for automatically identifying a plurality of joints within a body of a subject to monitor across a joint monitoring procedure. The method comprises: automatically receiving a predetermined set of joint identifiers, each joint identifier corresponding to a joint within the body; associating a score with each joint identifier in the predetermined set of joint identifiers; automatically selecting from the predetermined set of joint identifiers a plurality of joint identifiers based on the scores, wherein each selected joint identifier has a score equal to or higher than each non-selected joint identifier in the predetermined set of joint identifiers; storing each of the plurality of joint identifiers and the score associated therewith in an electronic database; and presenting visual and/or audio information corresponding to the plurality of joint identifiers on an electronic device for guiding the joint monitoring procedure.

According to a second aspect of the present disclosure, there is a system for automatically identifying a plurality of joints within a body of a subject to monitor across a joint monitoring procedure. The system comprises an electronic device for automatically receiving a predetermined set of joint identifiers, each joint identifier corresponding to a joint within the body; an inspection machine for determining and associating a score with each joint identifier in the predetermined set of joint identifiers; and an electronic database for storing a plurality of joint identifiers and the score associated therewith, the electronic database being accessible by the electronic device. The plurality of joint identifiers are automatically selected from the predetermined set of joint identifiers based on the scores, each selected joint identifier having a score equal to or higher than each non-selected joint identifier in the predetermined set of joint identifiers. Visual and/or audio information corresponding to the plurality of joint identifiers is presented on the electronic device for guiding the joint monitoring procedure.

An advantage of the present disclosure is that the most affected joints or joint sites of an individual patient are identified and selected for monitoring of disease activity, such as from rheumatoid arthritis, using a joint monitoring procedure or a set of joint monitoring procedures. The joints are identified and selected by associating a score to each joint, and thereby selecting the most affected joints. Another advantage is that because the identified and selected joints are the most affected ones, there is better responsiveness and improved sensitivity for detecting change in monitoring disease activity in the joints.

A method and system for automatically identifying a plurality of joints within a subject's body according to the present disclosure is thus disclosed hereinabove. Various features, aspects, and advantages of the present disclosure will become more apparent from the following detailed description of the embodiments of the present disclosure, by way of non-limiting examples only, along with the accompanying drawings in which like numerals represent like components.

Brief Description of the Drawings

FIG. 1 is a flow chart of a method according to an embodiment of the present disclosure. FIG. 2 is a flow chart of a step of the method in FIG. 1 , according to an embodiment of the present disclosure.

Detailed Description

In the present disclosure, depiction of a given element or consideration or use of a particular element number in a particular FIG. or a reference thereto in corresponding descriptive material can encompass the same, an equivalent, or an analogous element or element number identified in another FIG. or descriptive material associated therewith. The use of 7" in a FIG. or associated text is understood to mean "and/or" unless otherwise indicated. The recitation of a particular numerical value or value range herein is understood to include or be a recitation of an approximate numerical value or value range, for instance, within +/- 20%, +/- 15%, +/- 10%, +/- 5%, or +/- 0%. With respect to recitations herein directed to dimensional or numerical comparisons or equivalence, reference to the terms "generally," "approximately," or "substantially" is understood as falling within +/- 20%, +/- 15%, +/- 10%, +/- 5%, or +/- 0% of a representative / example comparison, or a specified or target value or value range; and reference to the term "essentially" is understood as falling within +/- 10%, +/- 5%, +/- 2%, +/- 1 %, or +/- 0% of a representative / example comparison, or a specified or target value or value range. As used herein, the term "set" corresponds to or is defined as a non-empty finite organization of elements that mathematically exhibits a cardinality of at least 1 (i.e., a set as defined herein can correspond to a unit, singlet, or single element set, or a multiple element set), in accordance with known mathematical definitions (for instance, in a manner corresponding to that described in An Introduction to Mathematical Reasoning: Numbers, Sets, and Functions, "Chapter 1 1 : Properties of Finite Sets" (e.g., as indicated on p. 140), by Peter J. Eccles, Cambridge University Press (1998)). In general, an element of a set can include or be a system, an apparatus, a device, a structure, an object, a process, a physical parameter, or a value depending upon the type of set under consideration.

For purposes of brevity and clarity, descriptions of embodiments of the present disclosure are directed to a method and system for automatically identifying a plurality of joints within a subject's body, in accordance with the drawings in FIG. 1 to FIG. 2. While aspects of the present disclosure will be described in conjunction with the embodiments provided herein, it will be understood that they are not intended to limit the present disclosure to these embodiments. On the contrary, the present disclosure is intended to cover alternatives, modifications and equivalents to the embodiments described herein, which are included within the scope of the present disclosure as defined by the appended claims. Furthermore, in the following detailed description, specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be recognized by an individual having ordinary skill in the art, i.e. a skilled person, that the present disclosure may be practiced without specific details, and/or with multiple details arising from combinations of aspects of particular embodiments. In a number of instances, well- known systems, methods, procedures, and components have not been described in detail as not to unnecessarily obscure aspects of the embodiments of the present disclosure.

In a representative or exemplary embodiment of the present disclosure, a method 100 for automatically identifying a plurality of joints within a body of a subject or a patient to monitor across a number of joint monitoring procedures (e.g., a plurality of joint monitoring procedures), as well as a system for automatically identifying the plurality of joints, is described hereinafter. As used herein throughout the present disclosure, the terms "automatic", "automatically", and the like shall refer to steps, methods, and/or processes that can be performed without human and/or manual intervention. The method 100, as well as the system thereof, is broadly described in a representative embodiment according to a flow chart as shown in FIG. 1 . In the method 100, step 1 10 includes automatically receiving a predetermined set of joint identifiers. Specifically, the predetermined set of joint identifiers is automatically received or retrieved by an electronic device or a computing device (e.g., a computer system or device such as a desktop, laptop, or tablet computer). The electronic / computing device includes processing resources and a memory storing program instructions that when executed by the processing resources facilitate or enable particular processes, procedures, and/or methods in accordance with an embodiment of the present disclosure. The electronic / computing resource can be configured for communication with one or more databases (e.g., portions of which can reside in the memory and/or on another type of data storage device), in a manner readily understood by individuals having ordinary skill in the relevant art.

Each joint identifier corresponds to a particular joint within the body of the subject under consideration. In some embodiments, the predetermined set of joint identifiers includes or consists of 44 joint identifiers and refers to a set of 44 joints for subsequent assessment and scoring. As such, each of the 44 joints corresponds to a joint identifier in the predetermined set of joint identifiers. In various embodiments, the 44 predetermined joints or joint identifiers are:

1 . Left shoulder joint

2. Right shoulder joint

3. Left elbow joint

4. Right elbow joint

5. Left wrist joint

6. Right wrist joint

7. Left metacarpophalangeal joint (MCPJ) 1

8. Left metacarpophalangeal joint (MCPJ) 2 9. Left metacarpophalangeal joint (MCPJ) 3

10. Left metacarpophalangeal joint (MCPJ) 4

1 1 . Left metacarpophalangeal joint (MCPJ) 5

12. Right metacarpophalangeal joint (MCPJ) 1 13. Right metacarpophalangeal joint (MCPJ) 2

14. Right metacarpophalangeal joint (MCPJ) 3 5. Right metacarpophalangeal joint (MCPJ) 4

16. Right metacarpophalangeal joint (MCPJ) 5

17. Left proximal interphalangeal joint (PIPJ) 2 18. Left proximal interphalangeal joint (PIPJ) 3

19. Left proximal interphalangeal joint (PIPJ) 4

20. Left proximal interphalangeal joint (PIPJ) 5

21 . Right proximal interphalangeal joint (PIPJ) 2

22. Right proximal interphalangeal joint (PIPJ) 3 23. Right proximal interphalangeal joint (PIPJ) 4

24. Right proximal interphalangeal joint (PIPJ) 5

25. Left thumb interphalangeal joint (IPJ)

26. Right thumb interphalangeal joint (IPJ)

27. Left hip joint

28. Right hip joint

29. Left knee joint

30. Right knee joint

31 . Left ankle joint

32. Right ankle joint

33. Left mid-tarsal joint

34. Right mid-tarsal joint

35. Left metatarsophalangeal joint (MTPJ) 1

36. Left metatarsophalangeal joint (MTPJ) 2

37. Left metatarsophalangeal joint (MTPJ) 3 38. Left metatarsophalangeal joint (MTPJ) 4

39. Left metatarsophalangeal joint (MTPJ) 5

40. Right metatarsophalangeal joint (MTPJ) 1

41 . Right metatarsophalangeal joint (MTPJ) 2 42. Right metatarsophalangeal joint (MTPJ) 3

43. Right metatarsophalangeal joint (MTPJ) 4

44. Right metatarsophalangeal joint (MTPJ) 5 For clarity purposes, the phalangeal joints 1 refer to the thumb; the phalangeal joints 2 refer to the index finger; the phalangeal joints 3 refer to the middle finger; the phalangeal joints 4 refer to the ring finger; and the phalangeal joints 5 refer to the little finger. It will be apparent to and readily understood by a person having ordinary skill in the art that the joint identifiers, and the number thereof, in the predetermined set of joint identifiers can be variable or modified (e.g., selectable, such as in response to user input directed to an input device of an electronic or computing device). The identified plurality of joints in the method 100 corresponds to or is represented by a subset of the predetermined set of joint identifiers, such that only a portion, particularly the most or likely most affected joints, is monitored across a joint monitoring procedure, such as for disease activities such as rheumatoid arthritis, or for another purpose such as monitoring progress. In the method 100, step 120 includes associating a score with each joint identifier in the predetermined set of joint identifiers. The score for each joint identifier can include at least one of a first score 122 and a second score 124. For instance, in a representative embodiment, the first score 122 is an ultrasound inflammatory score that is determined using ultrasound inspection equipment (e.g., an ultrasound or ultrasonography machine). More specifically, the first score 122 is determined by accessing database resident ultrasound scan results corresponding to each joint identifier in the predetermined set of joint identifiers. Each joint identifier names, identifies, or references a joint in the body of the subject. For example, the ultrasound or ultrasonography machine inspects or scans the joints of the subject's body, and the inspection or scan results are stored and reside in a database. The first score 122 is thus obtained by retrieving the scan results from the database. In a representative embodiment, the second score 124 is a clinical joint assessment score that is determined using a pain assessment, for each joint. Other forms or types of assessment of discomfort symptoms in the joints are possible, as would be readily known by the skilled person. More specifically, the second score 124 is determined by accessing database resident pain assessment results corresponding to each joint identifier in the predetermined set of joint identifiers for the subject under consideration. For example, the joints of the subject's body are assessed for symptoms such as tenderness, pain, and/or swelling. A score number is indicated for the assessment of each joint based on the severity of the symptoms, and the score numbers are stored and reside in a database. The second score 124 is thus obtained by retrieving the assessment results from the database.

In some embodiments, the method 100 uses only the first score 122, e.g., the ultrasound inflammatory score, for associating with each joint identifier. In some alternative embodiments, the method 100 uses both the first score 122 and the second score 124, e.g., the ultrasound inflammatory and clinical joint assessment scores, for associating with each joint identifier. It would be apparent to the skilled person that there can be other embodiments that use different variations and combinations of these and/or other scores for each joint identifier. Additionally, the scores (i.e. (1 ) the first score 122 or (2) both the first score 122 and the the second score 124) can be normalized or equalized, so as to scale the different scores of each joint identifier to a common or the same baseline.

The method 100 further includes a step 130 involving automatically selecting from the predetermined set of joint identifiers a plurality of joint identifiers based on the scores. Particularly, each selected joint identifier has a score equal to or higher than each non-selected joint identifier in the predetermined set of joint identifiers. The number of joints identified and selected for the plurality of joints of the subject's body can be predetermined at 7 or 12, for instance, according to the number of joints for existing ultrasound methods. Notably, studies have shown that using the predetermined 7 or 12 joints is reasonable, valid, and effective, based upon a systemic review of ultrasound joint counts and scoring systems for rheumatoid arthritis. However, it would be understood by the skilled person that the target joint count can be varied or modified, for instance, in accordance with embodiment details and/or an individual subject or patient under consideration. The method 100 further includes a step 150 involving storing each of the plurality of joint identifiers and the score associated therewith in an electronic database. One or more portions of the electronic database can reside within a data storage unit, a memory module, an online storage space, and the like. As indicated above, the electronic database can be coupled to or integrated with the electronic device or computing device, such that electronic database is accessible by the electronic or computing device. Consequently, information associated with the plurality of joint identifiers is accessible by the electronic or computing device. Additionally, the inspection machine, e.g., the ultrasound or ultrasonography machine, can be coupled to or integrated with the electronic or computing device, thereby allowing for communication of the ultrasound scores therewith.

The method 100 further includes a step 160 involving presenting visual and/or audio information corresponding to the plurality of joint identifiers using the electronic or computing device (e.g., on a display device / screen) for guiding the joint monitoring procedure. The information associated with the plurality of joint identifiers can thus be presented as visual and/or audio information using or on the electronic or computing device. Such presented information can advantageously guide and assist doctors, therapists, and/or clinicians to perform the joint monitoring procedure or a set of joint monitoring procedures. More particularly, the presented information about the plurality of joint identifiers that are selected from among the predetermined set of joint identifiers helps to identify the plurality of joints, i.e. the most affected joints, of a subject for monitoring (e.g., periodic monitoring involving multiple joint monitoring procedures). By preferentially identifying and monitoring the most affected joints (and correspondingly, thus avoiding monitoring lesser or least affected joints), there is better responsiveness and improved sensitivity for detecting changes over time in the joints of a subject under consideration, such as for monitoring changes in disease progression.

FIG. 2 shows a flow chart of step 130 of the method 100, particularly the automatic selection of the plurality of joint identifiers based on the scores. Step 130 includes a step 132 of ranking the joint identifiers (e.g., the 44 joint identifiers) in the predetermined set of joint identifiers by their scores. More specifically, all 44 joint identifiers can be ranked from a highest or maximum score to a lowest or minimum score. In some embodiments, this step 132 of ranking the predetermined joint identifiers can be omitted, as each joint identifier already has a score associated therewith.

Step 130 of the method 100 includes a step 134 involving selecting a first joint identifier from the predetermined set of joint identifiers, the first joint identifier having the highest or maximum score among the predetermined set of joint identifiers. In a step 136, the first joint identifier is discarded from the predetermined set of joint identifiers, thereby forming a remaining set of joint identifiers. In a step 138 that is similar to step 134, a second joint identifier is selected from the remaining set of joint identifiers, the second joint identifier having a maximum score among the remaining set of joint identifiers.

Steps 134, 136, and 138 for selecting the joint identifiers are repeated iteratively, or in an automated iterative process 140. Specifically, in the automated iterative process 140, the highest-scored joint identifier is selected from the predetermined set of joint identifiers, and the next highest-scored joint identifier is selected from the remaining set of joint identifiers.

In each of steps 134 and 138, the first and second joint identifiers, respectively, will be clearly apparent if there is only one joint identifier with the maximum score among their respective sets of joint identifiers. Step 130 of the method 100 includes a step 142 for determining whether there are multiple joint identifiers with the same maximum score. If there is only one joint identifier with the maximum score, then steps 134, 136, and 138 can continue as described above. However, if there are multiple joint identifiers with the same maximum score, the first joint identifier will be selected based on a predetermined sequence of joint identifiers, as indicated in a step 144 in FIG. 2. It will be apparent and readily understood by the skilled person that the second joint identifier can also be selected based on the predetermined sequence of joint identifiers. Accordingly, in various embodiments if there are multiple joint identifiers in the predetermined set of joint identifiers with the same maximum score, the first joint identifier is selected from the predetermined set of joint identifiers based on the predetermined sequence of joint identifiers. For example, if two joint identifiers share the same highest score, the joint identifier that is higher on the predetermined sequence is prioritized and selected. Each joint identifier represents each joint in the body of the subject. The predetermined sequence of joint identifiers follows from right then left at each joint of the subject's body, going from the smaller joints to medium joints and to the larger joints. The predetermined sequence for selecting the highest-scored joint identifiers from the 44 predetermined joint identifiers is as follows:

1 . Right metacarpophalangeal joint (MCPJ) 1

2. Right metacarpophalangeal joint (MCPJ) 2

3. Right metacarpophalangeal joint (MCPJ) 3

4. Right metacarpophalangeal joint (MCPJ) 4

5. Right metacarpophalangeal joint (MCPJ) 5

6. Left metacarpophalangeal joint (MCPJ) 1

7. Left metacarpophalangeal joint (MCPJ) 2

8. Left metacarpophalangeal joint (MCPJ) 3

9. Left metacarpophalangeal joint (MCPJ) 4

10. Left metacarpophalangeal joint (MCPJ) 5

1 1 . Right thumb interphalangeal joint (IPJ)

12. Right proximal interphalangeal joint (PIPJ) 2

13. Right proximal interphalangeal joint (PIPJ) 3

14. Right proximal interphalangeal joint (PIPJ) 4

15. Right proximal interphalangeal joint (PIPJ) 5

16. Left thumb interphalangeal joint (IPJ)

17. Left proximal interphalangeal joint (PIPJ) 2

18. Left proximal interphalangeal joint (PIPJ) 3

19. Left proximal interphalangeal joint (PIPJ) 4

20. Left proximal interphalangeal joint (PIPJ) 5

21 . Right metatarsophalangeal joint (MTPJ) 1 22. Right metatarsophalangeal joint (MTPJ) 2

23. Right metatarsophalangeal joint (MTPJ) 3

24. Right metatarsophalangeal joint (MTPJ) 4

25. Right metatarsophalangeal joint (MTPJ) 5

26. Left metatarsophalangeal joint (MTPJ) 1

27. Left metatarsophalangeal joint (MTPJ) 2

28. Left metatarsophalangeal joint (MTPJ) 3

29. Left metatarsophalangeal joint (MTPJ) 4

30. Left metatarsophalangeal joint (MTPJ) 5

31 . Right wrist joint

32. Left wrist joint

33. Right ankle joint

34. Left ankle joint

35. Right mid-tarsal joint

36. Left mid-tarsal joint

37. Right elbow joint

38. Left elbow joint

39. Right knee joint

40. Left knee joint

41 . Right shoulder joint

42. Left shoulder joint

43. Right hip joint

44. Left hip joint The predetermined sequence of joint identifiers corresponds to or follows from the smallest to largest joints, because disease activity, such as from rheumatoid arthritis, frequently affects or involves the smaller joints. Further, scanning of smaller joints is often easier. Yet further, semi-quantitative scoring system for synovitis was developed using the smaller joints, e.g. the fingers and toes.

Upon selection of the first joint identifier based on the predetermined sequence, the selected first joint identifier is discarded from the predetermined set of joint identifiers, according to step 136. A remaining set of joint identifiers is thereby formed. From the foregoing description, it will be apparent to the skilled person that the automated iterative process 140 can continue for subsequent iterations of selecting the joint identifiers. Accordingly, joint identifiers are selected based on decreasing scores and/or the predetermined sequence. As the selection can be primarily based on decreasing scores, each selected joint identifier has a score that is at least equal to, if not higher than, each non-selected joint identifier, i.e. the remaining set of joint identifiers.

The automated iterative process 140 continues and is repeated until the number of selected joint identifiers reaches a predetermined number. Thus, in a step 146, the automated iterative process 140 terminates or ends when the number of selected joint identifiers reaches the predetermined number. In various embodiments, the predetermined number or target joint count is typically 7 or 12, according to the number of joints for the existing ultrasound method.

The selected 7 or 12 joint identifiers correspond to 7 or 12 particular joints within the subject's body which will be subject to a set of joint monitoring procedures, such as multiple joint monitoring procedures performed over time. Notably, because the highest-scored joint identifiers are selected, the selected joint identifiers represent the most affected joints of a subject or patient. The joints can be monitored using a standardized response mean (SRM), which is a measure of responsiveness to treatment and estimates the magnitude of change of the scores in each of the selected joints over a fixed time period relative to the inherent variability among individual patients. The SRM results from the monitoring of joints selected using the method 100 highlights a greater potential to detect change(s) in disease activity over time, particularly because the selected joints are based on the individual patient's joint symptoms and/or ultrasound inflammatory findings.

Data based on the method 100 was collected from study analyses of patients diagnosed with rheumatoid arthritis. An objective of such study analyses was to determine whether the selection of joints using embodiments in accordance with the method 100 improves monitoring of disease activity in rheumatoid arthritis, as compared to existing ultrasound and DAS28 methods. Details and results of the study analyses are described hereinafter.

In a first study analysis, 10 study patients who are starting or escalating therapy or treatment of rheumatoid arthritis are selected. The 44 predetermined joints of each patient are assessed using clinical and ultrasound methods at the beginning, i.e., at 0 months, and at the end of 3 months, i.e., 3rd month. Various types of joint monitoring procedures are used for monitoring the joints. A first joint monitoring procedure involves monitoring the joints that are selected using the method 100, specifically the embodiment that uses only the first score 122 (ultrasound inflammatory score). A second joint monitoring procedure involves monitoring the joints that are selected using the method 100, specifically the embodiment that uses both the first score 122 and the second score 124 (clinical joint assessment score). As a benchmark, there is a third joint monitoring procedure which involves monitoring the joints that are predetermined as established by the existing ultrasound method, as well as a fourth joint monitoring procedure which involves monitoring the joints that are predetermined in the DAS28 method. Each of the first and second joint monitoring procedures involves a set of 7 joints or a set of 12 joints selected using embodiments of the method 100. The third joint monitoring procedure involves a set of 7 or 12 joints as predetermined by the existing ultrasound method. The fourth joint monitoring procedure involves a set of 28 joints as predetermined by the DAS28 method. Responsiveness or sensitivity to treatment was compared among the joint monitoring procedures using the SRM at the end of 3 months of the study.

The demographics or group profile of the 10 study patients are as follows:

Mean age (standard deviation): 58.6 years (4.4)

Gender: 80% female

Ethnicity: 80% Chinese; 10% Indian; and 10% of other ethnic groups

Mean disease duration (standard deviation): 65.1 months (77.7)

Mean baseline (DAS28): 5.16 The study patients are selected based on their DAS28 scores. The DAS28 is a composite score derived from some measures of disease activity in rheumatoid arthritis. A DAS28 score less than or equal to 2.6, i.e. DAS28 < 2.6, represents remission. A DAS28 score above 2.6 and less than or equal to 3.2, i.e. 2.6 < DAS28 < 3.2, represents low disease activity. A DAS28 score above 3.2 and less than or equal to 5.1 , i.e. 3.2 < DAS28 < 5.1 , represents moderate disease activity. A DAS28 score above 5.1 , i.e. DAS28 > 5.1 , represents high disease activity. The patients in this study all have a DAS28 score above 3.2, with the mean as 5.16. Each study patient is a seropositive rheumatoid arthritis subject with 5 or more tender and/or swollen joints initiated or escalated on disease-modifying anti-rheumatic drugs (DMARDs) and corticosteroid therapy. Notably, in order not to compromise on the accuracy of the results of the study, none of the study patients has any other connective tissue disease, inflammatory arthritis, juvenile inflammatory arthritis, pregnancy, known Hepatitis B & C, previous joint replacements, and/or previous limb amputation.

The joint monitoring procedure is performed at the beginning of the study i.e. at 0 month to set the baseline or reference benchmark, and at the end of the study, i.e. at the end of 3 months. The joint monitoring procedure includes a 44-joint clinical joint assessment that is performed by a metrologist, and an ultrasound evaluation that is performed on the same day. The ultrasound images are acquired and scored by a rheumatologist who is experienced and skilled in musculoskeletal ultrasonography. Additionally, the rheumatologist is blinded to the metrologist's clinical findings so as not to introduce any form of biasness. The 44 identified joints for monitoring are consistent with the aforementioned predetermined set of 44 joints.

In the clinical joint assessment performed by the metrologist, all 44 joints are assessed for tenderness and/or pain. Among the 44 joints, 40 of them are assessed for swelling. The bilateral hip and mid-tarsal joints are excluded from the swelling assessment. Joint tenderness and swelling are scored as 1 for yes and 0 for no. Joint pain was scored as 0 for none, 1 for mild, 2 for moderate, and 3 for severe. The relevant scores for each joint may be used in combination to generate a consolidated score that is equivalent to the aforementioned second score 124. In the ultrasound evaluation performed by the rheumatologist, ultrasound inspection or scanning was performed on the study patients using either the General Electric Healthcare LOGIQ e ultrasound machine with a multi-frequency linear array transducer (5 to 13 MHz) or the Philips Medical Systems EPIQ 5 ultrasound machine with a multi-frequency linear array transducer (5 to 17 MHz). For consistency, the ultrasound machines, probes, and settings for evaluating the joints are kept constant for each patient throughout the study. The ultrasound scanning was based on the EULAR OMERACT standardized definitions of ultrasound pathology.

The acquired ultrasound images are scored semi-quantitatively in increasing grades of severity for both grayscale synovial hypertrophy and power Doppler vascularity. A score of 0 refers to none or normal, 1 refers to mild, 2 refers to moderate, and 3 refers to severe. This scoring method or scale was used at the hand and feet joints and extrapolated for use in the other joints. However, for certain medium size joints, such as the elbow, knee, and ankle joints, where relevant images from a scoring altas are available, semi-quantitative scoring (also on a scale of 0 to 3) was performed based on the relevant images from the scoring atlas. Additionally, for both grayscale synovial hypertrophy and power Doppler vascularity, tenosynovitis was scored as either yes (1 ) or no (0). The relevant scores for each joint may be used in combination to generate a consolidated score that is equivalent to the aforementioned first score 122.

The joint monitoring procedure is performed at the beginning and the end of the study to evaluate the efficacy of treatment of rheumatoid arthritis. However, it would not be feasible and would be too time-consuming to continually monitor all 44 joints periodically. Thus, a subset of the predetermined set of 44 joints is identified and selected for the joint monitoring procedure. Each of the aforementioned first, second, third, and fourth joint monitoring procedures involves monitoring their respective subset of joints, as described hereafter.

The first joint monitoring procedure involves monitoring a set of 7 or 12 joints that are selected using the method 100 with the first score 122. The first joint monitoring procedure may otherwise be referred to as an individualized ultrasound (IUS) method. The method 100 involves associating a score, also known as an individual joint score (US), to each of the 44 joints. The method 100 involves the first score 122 which is the ultrasound inflammatory score. At each of the 44 joints, a consolidated ultrasound inflammatory score is obtained or calculated, such as from all the subcomponents of the ultrasound evaluation. The consolidated ultrasound inflammatory score of each of the 44 joints is then divided by the maximum score among all the 44 joints, thereby obtaining the US at each joint. The US in the IUS method is thus a normalized or equalized score that is weighted across all the joints, thereby scaling the scores to a common baseline. An affected joint is defined as having an US greater than 0, i.e. US > 0. The selected joints are thus the most ultrasonographically affected ones.

The second joint monitoring procedure may otherwise be referred to as an individualized composite ultrasound (ICUS) method. An US is also attributed to each of the 44 joints. The method 100 involves composite scoring that takes into account both the ultrasound inflammatory score (i.e. first score 122) and the clinical joint assessment score (i.e. second score 124). At each of the 44 joints, composite scoring which takes into account (A) consolidated ultrasound inflammatory score (such as from all the subcomponents of the ultrasound evaluation) as well as (B) consolidated clinical joint assessment score (such as from all the subcomponents of the clinical joint assessment). The objective is to assess which are the most affected joints (on both ultrasound and clinical joint assessment). At each of the 44 joints, the respective consolidated ultrasound inflammatory score and consolidated clinical joint assessment score are summed up to obtain a consolidated composite score. The consolidated composite score of each of the 44 joints is then divided by the maximum score among all the 44 joints, thereby obtaining the US at each joint. The US in the ICUS method is thus a normalized or equalized score that is weighted across all the joints, thereby scaling the scores to a common baseline. An affected joint is defined as US > 0.

The third joint monitoring procedure involves monitoring a set of 7 or 12 joints that are predetermined from the existing ultrasound methods. The 7 predetermined joints are as follows (on the subject's clinically dominant side only): wrist joints, MCPJs 2 & 3, PIPJs 2 & 3, and MTPJs 2 & 5. The 12 predetermined joints are as follows (on the bilateral sides of the subject): elbow joints, wrist joints, knee joints, ankle joints, and MCPJs 2 & 3. In the existing methods, the same set of 7 or 12 predetermined joints is used regardless of whether the subject or patient has inflammation in these joints. Analogous to the first joint monitoring procedure, an US is similarly obtained for each of the 7 or 12 predetermined joints, as would be readily understood by the skilled person. The fourth joint monitoring procedure involves monitoring a set of 28 joints that are predetermined from the DAS28 method. The 28 predetermined joints are as follows (on the bilateral sides of the subject): elbow joints, wrist joints, shoulder joints, knee joints, MCPJs 1 to 5, IPJs, and PIPJs 2 to 5. Like the existing methods, the same set of 28 predetermined joints is used regardless of whether the subject or patient has inflammation in these joints.

The following Table 1 shows a summarized comparison of the joints used for the joint monitoring procedures. Some of the acronyms mentioned in Table 1 are elaborated as follows. IUS refers to the individualized ultrasound method; ICUS refers to the individualized composite ultrasound method; ED means extensor digitorum; ECU means extensor carpi ulnaris; and FD means flexor digitorum.

Table 1 : Joint and tendon sites used in joint monitoring procedures

An objective of the studies is to determine whether a selected subset of joints would be sufficient and useful enough for continual monitoring, such that effectiveness of treatment of patients diagnosed with rheumatoid arthritis can be reasonably and accurately ascertained by evaluating the selected subset of joints, instead of an entire set of the 44 major joints. A statistical analysis involving certain statistical parameters are performed on the evaluation results based on joints that are selected in each of first, second, third, and fourth joint monitoring procedures. The statistical analysis is described hereinafter.

For the IUS, ICUS, and existing selection methods, the IJSs from the selected joints (7 or 12) were summed up to obtain a total inflammatory score (TIS) for each patient. Statistical parameters including mean TIS, standard deviation of TIS, median TIS, and interquartile range (IQR) between the 1 st and 3rd quartiles of TIS, among all the 10 patients were calculated at the 0th and 3rd month. The statistical parameters are subsequently used to calculate the standardized response mean (SRM). As mentioned above, the SRM measures responsiveness to treatment and estimates the magnitude of change of the TIS in the patients. Specifically, the SRM is calculated as the mean change in the TIS divided by the standard deviation of the change in the TIS. The resultant values of the SRM can often be interpreted using existing interpretation methods for effect sizes (ES), e.g. those developed by Jacob Cohen. ES < 0.20 represents trivial, 0.20 < ES < 0.50 represents small, 0.50 < ES < 0.80 represents moderate, and ES > 0.80 represents large.

As an additional comparison benchmark, some statistical parameters for joints selected using the DAS28 method were also calculated. The statistical parameters include the mean DAS28 scores at the 0th and 3rd month, and the resultant SRM value. Further, for each selection method, the average number of actual affected joints among the selected set of joints was calculated. This is to ascertain whether the selected set of joints, from each selection method, can accurately represent a substantial portion of the actual affected joints.

A summarized comparison of the statistical analysis is presented in Table 2 below.

Table 2: Statistical results of first study analysis on selected joints

In the 7-joint approach, the average numbers of affected joints are as follows: 7 for IUS, 7 for ICUS, and only 3 for existing. The magnitude values of the SRMs are as follows: 1 .16 for IUS, 1 .96 for ICUS, and 0.28 for existing. In the 12-joint approach, the average numbers of affected joints are as follows: 1 1 for IUS, 12 for ICUS, and only 8 for existing. The magnitudes of the SRMs are as follows: 1 .12 for IUS, 1 .53 for ICUS, 0.37 for existing. For comparison purposes, the magnitude value of the SRM for DAS28 is 0.84.

Additionally, the SRMs from the aforementioned existing methods are consistent with the SRMs from other rheumatoid arthritis studies. In one study, the magnitude of SRM was recorded as 0.2595 at the 5th month, utilizing ultrasound evaluation on a predetermined set of 10 joints (bilateral MCPJs 1 to 5). In another study, the magnitude of SRM was recorded as 0.46 at the 3rd month, utilizing ultrasound evaluation on the dominant wrist joint. As can be seen from the statistical analysis of this first study, there is a relatively higher success rate for identifying affected joints using the joint selection methods in IUS and ICUS, i.e. embodiments of the method 100. Further, the SRMs from the IUS and ICUS selection methods are relatively higher, in terms of magnitude, than the comparison SRMs (from existing and DAS28 methods). As such, the responsive to treatment is more apparent when the selected joints the IUS and ICUS methods are monitored.

To further verify the results of the first study, a second study analysis was conducted based on 12 patients with rheumatoid arthritis. The demographics or group profile of the 12 study patients are as follows:

Mean age (standard deviation): 57.6 years (6.5)

Gender: 83.3% female

Ethnicity: 83.3% Chinese; 8.3% Indian; and 8.3% of other ethnic groups

Mean disease duration (standard deviation): 55.8 months (71 .2)

Mean baseline (DSA28): 5.21

A summarized comparison of the statistical results of the second study analysis is presented in Table 3 below.

Mean TIS

2.70 1 .76

(standard 2.81 1.84 1 .46 1.27

- - (1 .61 ) (0.95)

deviation) (1 .20) (0.82) (0.80) (0.72)

Median 2.48 1 .60 2.74 1.75 1 .55 1.42

- - TIS (IQR) (1 .99) (1 .20) (1 .58) (1 .25) (1 .65) (1 .37)

SRM (95% -1 .00 (- -1 .16 (- -0.49 (- Confidence - 1 .69, - - 1.89, - - 1.09, - - Interval) 0.29) 0.40) 0.12)

Average

number of

- - - - - - - - affected

joints

Mean TIS

28 5.21 4.32 (standard - - - - - -

Joints (0.66) (1 .00) deviation)

(for

DAS28) Median

- - - - - - - - TIS (IQR)

SRM (95% -0.94 (- Confidence - - - - - - - 1.68, - Interval) 0.17)

Table 3: Statistical results of second study analysis on selected joints

In the 7-joint approach, the average numbers of affected joints are as follows: 7 for IUS, 7 for ICUS, and only 3 for existing. The magnitude values of the SRMs are as follows: 1 .08 for IUS, 1 .1 1 for ICUS, and 0.39 for existing. In the 12-joint approach, the average numbers of affected joints are as follows: 1 1 for IUS, 12 for ICUS, and only 7 for existing. The magnitudes of the SRMs are as follows: 1 .00 for IUS, 1 .16 for ICUS, 0.49 for existing. For comparison purposes, the magnitude value of the SRM for DAS28 is 0.94.

Similar to the first study analysis, the results in the second study analysis show that there are advantages in selecting joints using the IUS and ICUS methods. Particularly, there is a relatively higher success rate in identifying the actual affected joints, and the responsiveness to treatment is more apparent when monitoring the selected joints using the IUS and ICUS methods.

Therefore, based on the results of the study analyses, identifying and selecting joints within a subject's body using the method 100 substantially improves disease activity monitoring as compared to existing methods. Unlike the existing methods, the method 100 also performed better than DAS28. An advantage of selecting joints using the method 100 is that there is due consideration of an individual's joint symptoms and/or ultrasound inflammatory findings, such that the most affected (ultrasonographically inflamed and/or clinically symptomatic joints) are selected. As the number of actual affected joints is higher in the set of selected joints for monitoring, the potential to detect change in the disease activity over time also correspondingly increases. Experimental efficacy is improved, thereby resulting in better responsiveness and improved sensitivity for detecting changes from the monitoring of the joints. The joints that are identified and selected using the method 100 are sufficient to use as a small subset of joints of a subject's body for monitoring thereof. The set of joints are more likely to include a higher percentage of actual affected joints, and thus can better or much better represent an accurate affected-joints subset. Repeated / continued / continual / ongoing monitoring of the smaller selected set of joints yields better responsiveness and improved sensitivity for detecting change in monitoring symptom / disease activity in the joints. Unlike the existing ultrasound method, although the method 100 can require the entire set of 44 predetermined joints to be assessed at baseline prior to selection of the joints and thus require additional time, the assessment of the 44 joints is only performed once at the baseline stage. Subsequent assessment or evaluation or scans will only be performed on a small set of joints selected based on the method 100 for periodic or continued monitoring thereof. There are thus improved responsiveness and sensitivity of the repeated monitoring of the joints selected using the method 100, as compared to joints selected by the existing ultrasound and DAS28 methods. Using method 100 could therefore help reduce the sample size required in clinical trial, leading to time and cost savings.

The method 100 can also include correlation with other subject outcomes, such as disease remission, structural alteration, and/or functional prognosis. Embodiments of the present disclosure, including the method 100 and a system thereof that includes the aforementioned electronic / computing device, can be further extended to larger cohorts or populations. Yet further, the selection methods described in the present disclosure can be extended beyond rheumatoid arthritis conditions and to assess other subject symptoms, diseases, and/or illnesses.

In the foregoing detailed description, embodiments of the present disclosure in relation to a method and system for automatically identifying a plurality of joints within a subject's body are described with reference to the provided figures. The description of the various embodiments herein is not intended to call out or be limited only to specific or particular representations of the present disclosure, but merely to illustrate non-limiting examples of the present disclosure. The present disclosure serves to address at least some of the mentioned problems and issues associated with the prior art. Although only some embodiments of the present disclosure are disclosed herein, it will be apparent to a person having ordinary skill in the art in view of this disclosure that a variety of changes and/or modifications can be made to the disclosed embodiments without departing from the scope of the present disclosure. The scope of the disclosure as well as the scope of the following claims is not limited to embodiments described herein.

Claims

1 . A method for automatically identifying a plurality of joints within a body of a subject to monitor across a joint monitoring procedure, the method comprising:

automatically receiving a predetermined set of joint identifiers, each joint identifier corresponding to a joint within the body;

associating a score with each joint identifier in the predetermined set of joint identifiers;

automatically selecting from the predetermined set of joint identifiers a plurality of joint identifiers based on the scores, wherein each selected joint identifier has a score equal to or higher than each non-selected joint identifier in the predetermined set of joint identifiers;

storing each of the plurality of joint identifiers and the score associated therewith in an electronic database; and

presenting visual and/or audio information corresponding to the plurality of joint identifiers on an electronic device for guiding the joint monitoring procedure.

2. The method as in claim 1 , wherein each score comprises at least one of a first score and a second score.

3. The method as in claim 2, further comprising determining the first scores by accessing database resident ultrasound scan results corresponding to each body joint identifier in the predetermined set of joint identifiers.

4. The method as in claim 2 or 3, further comprising determining the second scores by accessing database resident pain assessment results corresponding to each joint identifier in the predetermined set of joint identifiers.

5. The method as in claim 2, wherein each of the first and second scores is normalized.

6. The method as in claim 1 , wherein selecting the plurality of joint identifiers comprises an automated iterative process.

7. The method as in claim 6, the automated iterative process comprising:

selecting a first joint identifier from the predetermined set of joint identifiers, the first joint identifier having a maximum score among the predetermined set of joint identifiers;

discarding the first joint identifier from the predetermined set of joint identifiers, thereby forming a remaining set of joint identifiers; and

selecting a second joint identifier from the remaining set of joint identifiers, the second joint identifier having a maximum score among the remaining set of joint identifiers.

8. The method as in claim 7, wherein if there are multiple joint identifiers in the predetermined set of joint identifiers with the same maximum score, the first joint identifier is selected based on a predetermined sequence of joint identifiers.

9. The method as in claim 7 or 8, wherein the automated iterative process ends when the number of selected joint identifiers reaches a predetermined number.

10. The method as in claim 1 or 6, further comprising ranking each joint identifier in the predetermined set of joint identifiers for selecting the plurality of joint identifiers.

1 1 . A system for automatically identifying a plurality of joints within a body of a subject to monitor across a joint monitoring procedure, the system comprising:

an electronic device for automatically receiving a predetermined set of joint identifiers, each joint identifier corresponding to a joint within the body; an inspection machine for determining and associating a score with each joint identifier in the predetermined set of joint identifiers; and

an electronic database for storing a plurality of joint identifiers and the score associated therewith, the electronic database being accessible by the electronic device, wherein the plurality of joint identifiers are automatically selected from the predetermined set of joint identifiers based on the scores, each selected joint identifier having a score equal to or higher than each non-selected joint identifier in the predetermined set of joint identifiers; and

wherein visual and/or audio information corresponding to the plurality of joint identifiers is presented on the electronic device for guiding the joint monitoring procedure.

12. The system as in claim 1 1 , the electronic device for performing an automated iterative process for selecting the plurality of joint identifiers.

13. The system as in claim 12, the automated iterative process comprising:

14. The system as in claim 13, wherein if there are multiple joint identifiers in the predetermined set of joint identifiers with the same maximum score, the first joint identifier is selected based on a predetermined sequence of joint identifiers.

15. The system as in claim 13 or 14, the electronic device further for ending the automated iterative process when the number of selected joint identifiers reaches a predetermined number.