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Record W2167360318 · doi:10.1186/2045-709x-19-2

SPECT/CT imaging of the lumbar spine in chronic low back pain: a case report

2011· article· en· W2167360318 on OpenAlexafffund
Michael Carstensen, Mashael Al-Harbi, Jean-Luc Urbain, Tarik Belhocine

Bibliographic record

VenueChiropractic & Manual Therapies · 2011
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsSt. Joseph's Hospital
FundersLondon Health Sciences Centre
KeywordsMedicineRadiologyLow back painLumbarFacet jointSingle-photon emission computed tomographyBack painNuclear medicinePositron emission tomographyLumbar vertebraePathology

Abstract

fetched live from OpenAlex

Mechanical low back pain is a common indication for Nuclear Medicine imaging. Whole-body bone scan is a very sensitive but poorly specific study for the detection of metabolic bone abnormalities. The accurate localisation of metabolically active bone disease is often difficult in 2D imaging but single photon emission computed tomography/computed tomography (SPECT/CT) allows accurate diagnosis and anatomic localisation of osteoblastic and osteolytic lesions in 3D imaging. We present a clinical case of a patient referred for evaluation of chronic lower back pain with no history of trauma, spinal surgery, or cancer. Planar whole-body scan showed heterogeneous tracer uptake in the lumbar spine with intense localisation to the right lateral aspect of L3. Integrated SPECT/CT of the lumbar spine detected active bone metabolism in the right L3/L4 facet joint in the presence of minimal signs of degenerative osteoarthrosis on CT images, while a segment demonstrating more gross degenerative changes was more quiescent with only mild tracer uptake. The usefulness of integrated SPECT/CT for anatomical and functional assessment of back pain opens promising opportunities both for multi-disciplinary clinical assessment and treatment for manual therapists and for research into the effectiveness of manual therapies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.313
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2011
Admission routes2
Has abstractyes

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