DOI: 10.5061/dryad.x3ffbg7zw
title: Total-body PET for assessing myofascial pain

description: 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).
description: # **Total-Body PET for Assessing Myofascial Pain** ## **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.