Background

Chronic low back pain due to myofascial pain syndrome is a widespread and debilitating condition, with substantial clinical and socioeconomic impact. Despite its prevalence, there remains a critical lack of objective and reproducible biomarkers for diagnosis and therapeutic assessment. Conventional methods for evaluating myofascial pain rely primarily on subjective clinician assessment and patient report, which are subject to high inter-observer variability and may provide only limited insight into tissue-level pathology.

This project leveraged total-body positron emission tomography/computed tomography (TB-PET/CT) using a dual-tracer approach: [11C]Butanol for tissue perfusion quantification and [18F]FDG for assessment of glucose metabolism and exploratorily, tissue perfusion. By integrating information from these tracers, the study aimed to dissect the biological underpinnings of painful versus non-painful myofascial tissues, with participant-reported outcomes collected simultaneously.

This study was funded by the National Institutes of Health, National Center for Complementary and Integrative Health, via grant R61 AT012187, titled: Total-body PET for assessing myofascial pain (PIs: Abhijit J Chaudhari; Lorenzo Nardo). More information is also available at ClinicalTrials.gov (NCT05876858).

Data Organization and Naming Convention

The study received explicit consent from study participants to publish de-identified data. Code numbers were assigned to the human subjects and data are completely de-identified. No identifiers are present in any form. Only code numbers are used in the uploaded data.

Imaging data within the Total-body_PET_Myofascial_Pain.zip file are organized in subject-specific folders using the structure:
[SubjectID]_[Radiotracer].
[SubjectID]: three-digit participant identifier (e.g., 079)
[Radiotracer]: either FDG for [18F]FDG, or BTL for [11C]Butanol

Within each folder, the following NRRD files are provided:
CT image: Sub[SubjectID]_[Radiotracer]CT_cropped.nrrd
PET image: Sub[SubjectID][Radiotracer]PT_cropped.nrrd
Segmentation (L4–S1 region): Sub[SubjectID][Radiotracer]_L4_S1.seg.nrrd

Example:
For subject 079 and butanol scan, filenames are:
Sub079_BTL_CT_cropped.nrrd
Sub079_BTL_PT_cropped.nrrd
Sub079_BTL_L4_S1.seg.nrrd

Clinical Measures
The repository includes a CSV file (PEG_Scores.csv) containing PEG (Pain, Enjoyment, General activity) scores for each participant.
The CSV provides breakdowns for all three PEG questions. The scores are matched to imaging folders via Subject ID.

File Specifications
Format: All image files are in .nrrd format.
PET images: Expressed in Bq/ml units, cropped to the lumbosacral region.
CT images: Attenuation-correction CT in Hounsfield Units, cropped to lumbosacral region.
Segmentations: Binary mask (1 = L4–S1, 0 = background).
SUV_Conversion_Factor.csv: CSV, subject-matched, to convert Bq/ml into PET SUV
PEG scores: CSV, subject-matched.

Technical Details

Scanner Model: All scans were performed on the EXPLORER total-body PET/CT scanner (United Imaging Healthcare), located at UC Davis.

Acquisition Protocol:
Tracers: [11C]Butanol and [18F]FDG
[11C]Butanol: Used to assess regional perfusion; dynamic TB-PET acquisition initiated at tracer injection.
[18F]FDG: Used to evaluate glucose metabolism and, via early framing, perfusion.

CT: Low-dose CT was acquired for attenuation correction prior to PET.

Imaging region: Acquisition covered the entire body; files provided are cropped to the lumbosacral region (L4–S1).

Duration: [11C]Butanol dynamic acquisition typically covered 10 minutes, [18F]FDG dynamic images were collected for up to 70 min.

Image Reconstruction: Images provided are over 50-65min for [18F]FDG and 1-5 min for [11C]Butanol, in Bq/ml
PET: Images reconstructed using OSEM (ordered subset expectation maximization), with time-of-flight and no point-spread function modeling. Standardized corrections applied for attenuation, scatter, and decay.
CT: Reconstructions generated in Hounsfield Units.
All images exported in NRRD format for interoperability with open-source analysis tools.

Segmentations:
L4–S1 paraspinal muscles were automatically segmented using MOOSE (PMID: 35772962) then manually curated by an experienced nuclear medicine physician on co-registered PET/CT using 3D Slicer, and exported as binary masks.

Citation

If you use this dataset, we encourage citing as:
"Chaudhari AJ, et al. Total-body PET for Assessing Myofascial Pain: multi-tracer dataset with lumbosacral segmentations and pain scores. Dryad Digital Repository (2025). https://doi.org/10.5061/dryad.x3ffbg7zw"

Human subjects data

The study has received explicit consent from study participants to publish de-identified data. Code numbers were assigned to the human subjects and data are completely de-identified. No identifiers are present in any form. Only code numbers are used in the uploaded data.