shapes and patterns in chronic pain colin r. taylor, md contributors: ccb: ivo dinov, byung-woo...

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).

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.

The First Pain Diagram (Albrecht Dürer ~1510)

TMT Pain Diagrams 2D & 3D models are “mapped” to each other.

2D (Front & Back Views)

“3D”: Rotating Model (24 Horizontal views & 24 Vertical views)

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

BPI and TMT Pain Diagrams Industry-standard design (BPI) “mapped” to

TMT design for pain data transfer.

Many Pain Diagram Designs Used in Clinical Practice

All can be mapped to TMT diagram

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!

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.

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

Face to Brain MappingSomatosensory Cortical Representation

Mapping ProblemPlantar Fasciitis (“Heel Spur”) can’t be drawn on BPI diagram

Dimiter Prodanov: Cylindrical Projection on a Plane

Conversion of 2D Knee Pain Data to 3D

Pfizer Study (N=587) Typical nociceptive (green) and neuropathic pain (blue)

have different locations.

Pain with Bone MetastasesPain location may identify bone metastases

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)

Knee Pain ShapesAnterior knee pain shows

lateral, central and medial clusters

CCB (Ivo Dinov) 2D Point Cluster Segmentation

Confirms lateral, central and medial clusters with anterior knee pain

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

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.

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)

TMT Shoulder Pain (N=55)Anterior pain is around tip of shoulder. Posterior pain includes back and neck.

2D TMT Shoulder Pain transferred to 3D Pain Drawing Model

Pfizer Study (N=587) Primary Care Subjects seen by Pain Specialists

Shoulder pain common (9% of all pain)

Shoulder Pain Distribution in 2 StudiesSimilar distribution in web TMT study (N=55)

& Pfizer primary care study (N=49)

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.

2D TMT Headache on 3D Pain Drawing Model

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

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.

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.

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.

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