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Shapes and Patterns in Chronic Pain
Colin R. Taylor, MD
Contributors:
CCB: Ivo Dinov, Byung-Woo Hong, Haiyong Xu: Cluster segmentation of knee pain data using mixture modeling & expectation maximization (EM), Principal Components Analysis (PCA), Test for geometric/clinical correlations.
Igor Zhukovsky and Vladimir Bulan: 2D and 3D pain drawing applets, Triangulation-based image-to-image mapping. Web-based medical questionnaires.
Dimiter Prodanov: Cylindrical projections for 2D/3D knee pain data conversion.
F. James Rohlf: Isodensity plots, TPS mapping, geometric morphometrics.
Colin J. Taylor: (My son) Automated pain diagram coregistration, pain shape outline identification, composite image generation, ImageJ-measured geometric variables. C++ (prototyped in MatLab).
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Introduction
• TMT (Taylor MicroTechnology, Inc.) is a small medical devices & consulting company incorporated in 1984.
• Academic Collaborations: CCB and others.
• Need: Better evaluation & management of pain.
• Technology: – Digitized (web-based or single computer) pain diagrams.– Legacy paper copies of pain diagrams (which are then digitized).– Computer-based visualization and analysis of pain diagrams.– 2D/3D mapping. Map Legacy diagrams to TMT diagram.
• Goal: Routine use of pain diagrams to manage pain.
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The First Pain Diagram (Albrecht Dürer ~1510)
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TMT Pain Diagrams 2D & 3D models are “mapped” to each other.
2D (Front & Back Views)
“3D”: Rotating Model (24 Horizontal views & 24 Vertical views)
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Live Web Demos Show TMT’s 2D & 3D Models in Action
• 2D Pain Questionnaire (knee pain)– Knee Pain Questionnaire– Example Report
• 3D Pain Drawing Model – 3D Model
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BPI and TMT Pain Diagrams Industry-standard design (BPI) “mapped” to
TMT design for pain data transfer.
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Many Pain Diagram Designs Used in Clinical Practice
All can be mapped to TMT diagram
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TMT-B-011 Pain QuestionnairesLarge, inexpensive, web-based study
• ClinicalTrials.gov NCT00284245 – TMT-B-011
• Over 3,700 of 10,000 IRB-approved subjects recruited.
• Rapid and inexpensive: ~ $1.50/subject!
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Mapping AlgorithmsTriangulation method preferred
• Thin-Plate Spline (TPS) – Interpolation function that minimizes "bending
energy." Theoretically attractive but limited by user interface.
• Triangulation – Set of paired triangles linking corresponding
parts of body in two diagrams. Linear transformation of points within a triangle. For 2D/3D mapping, 2D points are mapped to appropriate 2D view of the 3D model.
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2D Mapping ExamplesTMT/Bony Skeleton & TMT/BPI
TMT Bony Skeleton TMT/Skeleton BPI BPI/TMT
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Dermatomes Mapped to TMT DiagramRelates TMT body pain to spinal nerve roots
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Face to Brain MappingSomatosensory Cortical Representation
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Mapping ProblemPlantar Fasciitis (“Heel Spur”) can’t be drawn on BPI diagram
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Dimiter Prodanov: Cylindrical Projection on a Plane
Conversion of 2D Knee Pain Data to 3D
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Pfizer Study (N=587) Typical nociceptive (green) and neuropathic pain (blue)
have different locations.
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Pain with Bone MetastasesPain location may identify bone metastases
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Primary Care vs. Bone Metastasis PainMetastatic pain more common in red areas: pelvis, lower back, ribs,
neck? (need to adjust analysis/display for confounding variables)
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Knee Pain ShapesAnterior knee pain shows
lateral, central and medial clusters
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CCB (Ivo Dinov) 2D Point Cluster Segmentation
Confirms lateral, central and medial clusters with anterior knee pain
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Cylindrical 3D Transformation of Front and Back Knee Pain Centroids (Prodanov)
Shows feasibility of cylindrical assumption approach – results can be compared with those from other TMT 2D/3D mapping
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CCB Geometric/Clinical CorrelationsSize of pain shape area
predictive of more severe pain
Pain Shape Area: Preliminary hypothesis-generation analysis found highly significant (P<.0001) positive correlations with:• More severe pain.• Poorer quality of life• Other clinical measures of pain (e.g., pain quality,
associated symptoms, precipitants of pain, therapeutic response, and underlying diagnosis).
• Probable (p<.001) increase in females.
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Gender & Widespread PainWidespread pain (of which fibromyalgia is a subset) is
much more common in females
42 Women (531 pain shapes) 13 Men (157 pain shapes) (12.6/woman) (12.1/man)
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TMT Shoulder Pain (N=55)Anterior pain is around tip of shoulder. Posterior pain includes back and neck.
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2D TMT Shoulder Pain transferred to 3D Pain Drawing Model
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Pfizer Study (N=587) Primary Care Subjects seen by Pain Specialists
Shoulder pain common (9% of all pain)
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Shoulder Pain Distribution in 2 StudiesSimilar distribution in web TMT study (N=55)
& Pfizer primary care study (N=49)
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TMT Headache Study (N=54)Anterior headache over eyes and forehead and sides of head.
Posterior headache localized to neck and center of back of head
29% Migraine, 18% Tension Headache, 14% Sinusitis, 39% Other.
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2D TMT Headache on 3D Pain Drawing Model
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Human vs. Computer AnalysisSome human preprocessing useful
• Computer algorithms for pain edge detection OK for aggregate analysis, but not for individual patients (who often do not follow drawing instructions).
• Blinded analysis avoids bias in human editing.
• Library of atypical pain shapes kept to ensure standardization in human editing
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Pain Patterns
• Pain Pattern = Composite of features that collectively indicate or characterize a pain syndrome or disease.
• Mine Data for Patterns: Mine TMT’s rich pain datasets containing geometric morphometric and clinical variables to identify pain patterns (even in absence of diagnosis).
• Correlate Patterns with Diagnoses: Where diagnosis available, identify pain pattern that predicts the disease.
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General Project Challenges
• Access Existing Databases: Obtain access to existing pain diagram databases (estimated to contain several million patients with chronic pain).
• Collaborate with Academic Centers: Incorporate TMT pain diagram technology in patient workup at academic centers.
• FUNDING: Obtain funding to speed up research.
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Computational & Statistical Challenges
• More Mapping: Technology to map 2D/3D pain shape data to brain MRI data and to other internal structural/functional body entities.
• Use Pain Patterns: Pain “patterns” to classify patients into diagnostic, therapeutic and prognostic groups.
• Robust Statistics: Statistical methodology to establish clinical value of pain patterns.
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Summary
• Novel, robust, inexpensive methodology for recording/analysis of pain diagrams.
• Established clinical value of approach:– Differentiation of neuropathic & nociceptive
pain.– Evaluation of bone metastasis pain.– Large web-based chronic pain study.
• Continuation and extension of academic collaborations critical to rapid development