Data from: Systematic evaluation of magnetic particle imaging quantification strategies in biologically relevant scenarios using anatomically correct 3D printed mouse phantoms
Data files
Jul 27, 2026 version files 6.42 GB
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README.md
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Valdes_et_al_Systematic_Evaluation.zip
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Abstract
This dataset contains images of a mouse phantom used to evaluate segmentation methods in magnetic particle imaging (MPI) under biomedically-relevant conditions. The dataset includes MPI images of a mouse phantom with 100 ugFe in the liver cavity and various test masses (ranging from 0 to 2.5 ugFe) in the brain, hind flank and lung regions of interest (ROI). The 2D and 3D MPI images are provided in .nrrd format and segmentations of the ROI signal in .seg.nrrd format. Data were obtained using MOMENTUM Magnetic Particle Imaging Scanner (Magnetic Insight) and a lab-made iron oxide tracer coated with nDPEG. The phantom models used for 3D printing (brain and lung ports + liver and hind flank cavities) are provided in STL format, as well as another model that contains brain, lung, liver and hind flank anatomical cavities. A registered computed tomography (CT) image of all phantom configurations is also provided. The dataset is organized into folders containing the imaging data (.nrrd), folders containing tabular data (.txt) plotted in the article and the phantom models (.stl). The imaging data consist of each dataset that was studied (brain, flank and lung) and folders with additional data such as the reference samples that were used to calibrate signal into iron mass. and the models. This dataset has broader relevance for advancing quantitative imaging techniques in MPI for magnetic nanoparticle biodistribution studies.
Name: Carlos M. Rinaldi-Ramos, Ph.D.
Institution: University of Florida
Email: carlos.rinaldi@ufl.edu
Name: Daniela P. Valdés, Ph.D.
Institution: University of Florida
Email: d.valdes@ufl.edu
Dataset Overview
This dataset supports the publication "Systematic Evaluation of Magnetic Particle Imaging Quantification Strategies in Biologically Relevant Scenarios Using Anatomically Correct 3D Printed Mouse Phantoms" and includes data on mouse phantoms with a liver cavity filled with 100 ugFe and 0-2.5 ugFe in an ROI. The ROIs studied in the presence of the strong liver signal were: brain, hind flank and lung. The experiments were designed to evaluate different ROI segmentation methods and quantification from them. The files provided include imaging data and segmentation of the ROIs, STL files of 3D printed phantoms and the phantom bed designed to hold them, as well as characterization data for the particles used.
Dates of Data Collection
Data was collected in August 2025.
Funding
This work was supported by the National Institutes of Health (NIH) through the National Institute for Biomedical Imaging and Bioengineering (NIBIB) under award number R01EB031224, the National Cancer Institute (NCI) under award numbers R01CA298804 and R21CA263653, and the National Institute of Neurological Disorders and Stroke (NINDS) under award number R21NS125089.
Data Sources
All data were derived from MPI and CT imaging of mouse phantoms collected in August 2025 by the authors in MOMENTUM and IVIS SpectrumCT scanners, respectively. The MPI images are 2D/3D scans comprising 1/35 projections, acquired with a gradient of 5.7 T/m and an excitation field of 16/19 mT in the x/z channels. The MPI and CT .nrrds in this dataset were obtained after loading the .dcms (output from scanners) into 3D Slicer (Slicer 5.8.1) and using a transformation matrix to take them to the same coordinate space and be able to overlay them.
Description of the data and file structure
Parent folder structure
The folder Valdes_et_al_Systematic_Evaluation.zip was uploaded as a .zip. All the data for the manuscript is inside this zip file. Upon extraction, the folder presents the following structure:
Valdes_et_al_Systematic_Evaluation
├── Models
│ ├── Bed
│ ├── Brain and Lung Cavities
│ ├── Brain and Lung Ports
│ └── Flank and Flank Insert
├── MPI and CT imaging
│ ├── Brain dataset
│ │ ├── Brain_0-00_ugFe
│ │ ├── Brain_0-05_ugFe
│ │ ├── Brain_0-10_ugFe
│ │ ├── Brain_0-25_ugFe
│ │ ├── Brain_0-50_ugFe
│ │ ├── Brain_1-00_ugFe
│ │ ├── Brain_1-75_ugFe
│ │ └── Brain_2-50_ugFe
│ ├── Flank dataset
│ │ ├── Flank_0-00_ugFe
│ │ ├── Flank_0-05_ugFe
│ │ ├── Flank_0-10_ugFe
│ │ ├── Flank_0-25_ugFe
│ │ ├── Flank_0-50_ugFe
│ │ ├── Flank_1-00_ugFe
│ │ ├── Flank_1-75_ugFe
│ │ └── Flank_2-50_ugFe
│ ├── Lung dataset
│ │ ├── Lung_0-00_ugFe
│ │ ├── Lung_0-05_ugFe
│ │ ├── Lung_0-10_ugFe
│ │ ├── Lung_0-25_ugFe
│ │ ├── Lung_0-50_ugFe
│ │ ├── Lung_1-00_ugFe
│ │ ├── Lung_1-75_ugFe
│ │ └── Lung_2-50_ugFe
│ └── Reference samples
│ ├── Capillaries
│ │ ├── Capillary_0-00_ugFe
│ │ ├── Capillary_0-05_ugFe
│ │ ├── Capillary_0-10_ugFe
│ │ ├── Capillary_0-25_ugFe
│ │ ├── Capillary_0-50_ugFe
│ │ ├── Capillary_1-00_ugFe
│ │ ├── Capillary_1-75_ugFe
│ │ └── Capillary_2-50_ugFe
│ └── Cavities
│ ├── Cavity_0-00_ugFe
│ ├── Cavity_0-05_ugFe
│ ├── Cavity_0-10_ugFe
│ ├── Cavity_0-25_ugFe
│ ├── Cavity_0-50_ugFe
│ ├── Cavity_1-00_ugFe
│ ├── Cavity_1-75_ugFe
│ └── Cavity_2-50_ugFe
└── Plot data
├── Figure 3
├── Figure 5
├── Figure 7
├── Figure S1
│ └── TEM images
├── Figure S4
│ ├── Panel S4A
│ ├── Panel S4B
│ ├── Panel S4C
│ └── Panel S4D
├── Figure S7
│ ├── Panel S7A
│ ├── Panel S7B
│ ├── Panel S7C
│ ├── Panel S7D
│ ├── Panel S7E
│ └── Panel S7F
└── Figure S8
├── Panel S8A
├── Panel S8B
├── Panel S8C
├── Panel S8D
├── Panel S8E
└── Panel S8F
Overview of contents
| Section | Contents |
|---|---|
| Models | .stl files for the 3D-printed mouse phantoms, interchangeable anatomical components for capillary or cavity filling (brain, lung, and flank), and the phantom bed. |
| MPI and CT imaging | Registered CT and MPI image volumes (.nrrd) and corresponding ROI segmentation files (.seg.nrrd) for all phantom configurations. Includes brain, lung, flank, and reference sample datasets. |
| Plot data | Source data used to generate all figures and supplementary figures in the associated publication, including characterization data, calibration curves, and quantification results. |
Imaging datasets
| Dataset | ROI | Iron mass in ROI | Liver loading | Files provided |
|---|---|---|---|---|
| Brain | 0.8 mm id* capillary | 0-2.5 ugFe | 100 ugFe | CT, 2D/3D MPI, segmentation from 2D/3D MPI and CT |
| Lung | 0.8 mm id capillary | 0-2.5 ugFe | 100 ugFe | CT, 2D/3D MPI, segmentation from 2D/3D MPI and CT |
| Flank | 65.45 uL cavity | 0-2.5 ugFe | 100 ugFe | CT, 2D/3D MPI, segmentation from 2D/3D MPI and CT |
| Reference samples | Capillaries and 65.45 uL cavities | 0-2.5 ugFe | None | 2D/3D MPI, segmentation from 2D/3D MPI |
*id: inner diameter
Details
Models
.stl files of the phantom models and their beds. The Brain and Lung datasets were acquired using the models in the folders "Brain and Lung Ports". For the acquisition of the Flank dataset, the "Phantom Bottom" part was changed for the "Phantom Bottom with Flank Tumor Insert" and the "Phantom Flank Tumor - 65.45uL" model was placed in it. Additional removable tumor models with other volumes are named "Phantom Flank Tumor - #uL.stl, # being a placeholder for the value. Additional models with anatomical cavities instead of ports are provided in the "Brain and Lung Cavities" folder.
MPI and CT imaging
Contains the MPI and CT images of all the phantom configuration studied in .nrrds as well as the segmentation of the ROI signal studied. Three quantification from segmentation strategies were evaluated: (1) Threshold: a 50 % of maximum MPI signal threshold, (2) CV: a constant-volume segmentation matched to the volume of the threshold segmentation obtained from the 1 ug Fe reference signal, and (3) CVS: the CV segmentation used to get a subtraction of the MPI signal measured in the corresponding 0 ug Fe ROI. Different percentages of the threshold volume were also evaluated for CV and CVS and denoted Method%, with % being a placeholder for the % value, what we call CV and CVS are in reality CV100 and CVS100 because they have the same volume (100 %) than the 1ug Threshold signal.
Brain dataset
MPI and CT images of a mouse phantom with the liver cavity filled with 100 ugFe and X amount of ugFe in a 0.8 mm internal diameter capillary in the brain port. Subfolder structure is "Brain_X_ugFe", indicating the amount in each configuration. Note: Decimal points in folder names were replaced with hyphens (e.g., 0.25 is written as 0-25). A segmentation containing the segments obtained for the brain MPI signal through multiple methods, the 50 % of the maximum of the liver MPI signal, the body of the phantom from CT are provided in .seg.nrrd format for each configuration.
Flank dataset
MPI and CT images of a mouse phantom with the liver cavity filled with 100 ugFe and X amount of ugFe in a 65 uL cavity in the hind flank. Subfolder structure is "Flank_X_ugFe", indicating the amount in each configuration. Note: Decimal points in folder names were replaced with hyphens (e.g., 0.25 is written as 0-25). A segmentation containing the segments obtained for the flank MPI signal, the liver MPI signal, the body of the phantom from CT are provided in .seg.nrrd format for each configuration.
Lung dataset
MPI and CT images of a mouse phantom with the liver cavity filled with 100 ugFe and X amount of ugFe in a 0.8 mm internal diameter capillary in the lung port. Subfolder structure is "Lung_X_ugFe", indicating the amount in each configuration. Note: Decimal points in folder names were replaced with hyphens (e.g., 0.25 is written as 0-25). A segmentation containing the segments obtained for the lung MPI signal, the liver MPI signal, the body of the phantom from CT are provided in .seg.nrrd format for each configuration.
Reference samples
MPI images of capillaries and 65.45uL cavities filled with X amount of ugFe, which can be used as reference samples for quantification. Subfolder structure is "Type_X_ugFe", Type being Capillary or Cavity and X indicating the amount in each configuration. Note: Commas were replaced with "-". A segmentation containing the segments obtained for the reference sample MPI signal is provided in .seg.nrrd format for each iron mass.
Plot data
This folder contains tabular data for all the plots in the article and Supplementary Material. The subfolders are named as "Figure_#" and if divided into panels, subfolders named "Panel #Q" are present, with Q denoting the letter labeling the panel. Figures 3, 5, 7 correspond to parity plots of Quantified Iron Mass [ugFe] vs. Nominal Iron Mass [ugFe] for the different segmentation methods Threshold, CV and CVS, respectively. Figure S1 contains the characterization of the nDPEG particles, including transmission electron microscopy (TEM) and MPI Relax scans, with a subfolder containing all of the TEM images of the sample. Figure S4 contains the Iron Mass [ugFe] vs. Signal [arb.u.] data for the different methods and types of reference samples, named as Method_Type_2D/3D.txt. Finally, Figures S7 and S8 contain parity plots for the different percentage CV and CVS, denoted as Method%_Dataset_2D/3D.txt.
| Figure | Data provided | Brief description | Data provided and units |
|---|---|---|---|
| Figure 3 in article | Plot data | Threshold segmentation results for the brain, flank, and lung datasets, including representative MPI images and quantified iron mass versus nominal iron mass for 2D and 3D acquisitions. | Plot source data used to generate the figure (.txt), unit for all columns in ugFe. |
| Figure 5 in article | Plot data | Quantified iron mass versus nominal iron mass using the Constant Volume (CV = CVS100) segmentation approach for the brain, flank, and lung datasets, with Threshold results included for comparison. | Plot source data used to generate the figure (.txt), unit for all columns in ugFe. |
| Figure 7 in article | Plot data | Quantified iron mass versus nominal iron mass using the Constant Volume with Subtraction (CVS = CVS100) segmentation approach for the brain, flank, and lung datasets, with Threshold and CV results included for comparison. | Plot source data used to generate the figure (.txt), unit for all columns in ugFe. |
| Figure S1 in Supplementary Material | TEM images; Plot data | TEM images, particle size distribution, and MPI Relax scan data used to characterize the magnetic nanoparticles. | TEM images (.tif) and plot source data. For the histogram (.txt), the diameter's unit is nm. For MPI Relax (.dat), including negative and positive collinear and their fits, the field is in mT and the intensity in arbitrary units. |
| Figure S4 in Supplementary Material | Plot data (Panels S4A–S4D) | Calibration data relating nominal iron mass to total MPI signal for the reference samples (capillaries and cavities) used for quantification. | Plot source data for each panel (.txt). Signal is in arbitrary units and Nominal Iron Mass in ugFe. |
| Figure S7 in Supplementary Material | Plot data (Panels S7A–S7F) | Constant Volume at different percentages (CV10 to CV100) quantification results for the brain, flank, and lung datasets from 2D and 3D acquisitions, with Threshold results included for comparison. | Plot source data organized by panel (.txt), unit for all columns in ugFe. |
| Figure S8 in Supplementary Material | Plot data (Panels S8A–S8F) | Constant Volume with Subtraction at different percentages (CVS10 to CVS100) quantification results for the brain, flank, and lung datasets from 2D and 3D acquisitions, with Threshold and CV results included for comparison. | Plot source data organized by panel (.txt), unit for all columns in ugFe. |
Columns and units in tabular data
└── Plot data
├── Figure 3
│ ├── Threshold_Brain_3D_and_2D.txt
│ ├── Threshold_Flank_3D_and_2D.txt
│ └── Threshold_Lung_3D.txt
│ The files contain columns
│ Nominal Iron Mass [ug]: Iron mass put into the each ROI (Brain, Flank, Lung)
│ Iron Mass 3D/2D [ug]: Iron mass quantified from 3D/2D with the threshold segmentation.
│ Iron Mass 3D/2D Error [ug]: Error propagated from the 3D/2D reference sample fits.
├── Figure 5
│ ├── CV100_Brain_3D_and_2D.txt
│ ├── CV100_Flank_3D_and_2D.txt
│ └── CV100_Lung_3D_and_2D.txt
│ The files contain columns
│ Nominal Iron Mass [ug]: Iron mass put into each ROI (Brain, Flank, Lung)
│ Iron Mass 3D/2D [ug]: Iron mass quantified from 3D/2D with the CV100 segmentation.
│ Iron Mass 3D/2D Error [ug]: Error propagated from the 3D/2D reference sample fits.
├── Figure 7
│ ├── CVS100_Brain_3D_and_2D.txt
│ ├── CVS100_Flank_3D_and_2D.txt
│ └── CVS100_Lung_3D_and_2D.txt
│ The files contain columns
│ Nominal Iron Mass [ug]: Iron mass put into each ROI (Brain, Flank, Lung)
│ Iron Mass 3D/2D [ug]: Iron mass quantified from 3D/2D with the CVS100 segmentation.
│ Iron Mass 3D/2D Error [ug]: Error propagated from the 3D/2D reference sample fits.
├── Figure S1
│ ├── TEM images
│ ├── MPI_Relax_data_and_fits_12ugFe.dat
│ │ The file contain columns
│ │ B_pos/neg [mT]: Magnetic field offset
│ │ Signal_pos/neg: Signal for positive/negative collinear measurements, in arb. u.
│ │ Fit_pos/neg: Langevin derivative fit for positive/negative collinear measurements, in arb. u.
│ └── TEM_histogram.txt
│ The file contains columns
│ Image: Original image in the TEM images folder where the particle was measured.
│ Area [nm2]: Circular area of the particle measured.
│ Diameter [nm]: Diameter of the particle measured.
├── Figure S4
│ ├── Panel S4A
│ │ ├── CV100_Capillaries_2D.txt
│ │ └── Threshold_Capillaries_2D.txt
│ ├── Panel S4B
│ │ ├── CV100_Capillaries_3D.txt
│ │ └── Threshold_Capillaries_3D.txt
│ ├── Panel S4C
│ │ ├── CV100ug_Cavities_2D.txt
│ │ └── Threshold_Cavities_2D.txt
│ └── Panel S4D
│ ├── CV100_Cavities_3D.txt
│ └── Threshold_Cavities_3D.txt
│ The files from Figure S4 contain columns
│ Signal: Total signal inside the Threshold/CV100 segmentation of Capillary/Cavity reference sample scans.
│ Iron Mass [ug]: Nominal iron mass put into the Capillary/Cavity.
├── Figure S7
│ ├── Panel S7A
│ │ ├── CV10_Brain_2D.txt
│ │ ├── CV20_Brain_2D.txt
│ │ ├── CV30_Brain_2D.txt
│ │ ├── CV40_Brain_2D.txt
│ │ ├── CV50_Brain_2D.txt
│ │ ├── CV60_Brain_2D.txt
│ │ ├── CV70_Brain_2D.txt
│ │ ├── CV80_Brain_2D.txt
│ │ └── CV90_Brain_2D.txt
│ ├── Panel S7B
│ │ ├── CV10_Brain_3D.txt
│ │ ├── CV20_Brain_3D.txt
│ │ ├── CV30_Brain_3D.txt
│ │ ├── CV40_Brain_3D.txt
│ │ ├── CV50_Brain_3D.txt
│ │ ├── CV60_Brain_3D.txt
│ │ ├── CV70_Brain_3D.txt
│ │ ├── CV80_Brain_3D.txt
│ │ └── CV90_Brain_3D.txt
│ ├── Panel S7C
│ │ ├── CV10_Flank_2D.txt
│ │ ├── CV20_Flank_2D.txt
│ │ ├── CV30_Flank_2D.txt
│ │ ├── CV40_Flank_2D.txt
│ │ ├── CV50_Flank_2D.txt
│ │ ├── CV60_Flank_2D.txt
│ │ ├── CV70_Flank_2D.txt
│ │ ├── CV80_Flank_2D.txt
│ │ └── CV90_Flank_2D.txt
│ ├── Panel S7D
│ │ ├── CV10_Flank_3D.txt
│ │ ├── CV20_Flank_3D.txt
│ │ ├── CV30_Flank_3D.txt
│ │ ├── CV40_Flank_3D.txt
│ │ ├── CV50_Flank_3D.txt
│ │ ├── CV60_Flank_3D.txt
│ │ ├── CV70_Flank_3D.txt
│ │ ├── CV80_Flank_3D.txt
│ │ └── CV90_Flank_3D.txt
│ ├── Panel S7E
│ │ ├── CV10_Lung_2D.txt
│ │ ├── CV20_Lung_2D.txt
│ │ ├── CV30_Lung_2D.txt
│ │ ├── CV40_Lung_2D.txt
│ │ ├── CV50_Lung_2D.txt
│ │ ├── CV60_Lung_2D.txt
│ │ ├── CV70_Lung_2D.txt
│ │ ├── CV80_Lung_2D.txt
│ │ └── CV90_Lung_2D.txt
│ └── Panel S7F
│ ├── CV10_Lung_3D.txt
│ ├── CV20_Lung_3D.txt
│ ├── CV30_Lung_3D.txt
│ ├── CV40_Lung_3D.txt
│ ├── CV50_Lung_3D.txt
│ ├── CV60_Lung_3D.txt
│ ├── CV70_Lung_3D.txt
│ ├── CV80_Lung_3D.txt
│ └── CV90_Lung_3D.txt
└── Figure S8
├── Panel S8A
│ ├── CVS10_Brain_2D.txt
│ ├── CVS20_Brain_2D.txt
│ ├── CVS30_Brain_2D.txt
│ ├── CVS40_Brain_2D.txt
│ ├── CVS50_Brain_2D.txt
│ ├── CVS60_Brain_2D.txt
│ ├── CVS70_Brain_2D.txt
│ ├── CVS80_Brain_2D.txt
│ └── CVS90_Brain_2D.txt
├── Panel S8B
│ ├── CVS10_Brain_3D.txt
│ ├── CVS20_Brain_3D.txt
│ ├── CVS30_Brain_3D.txt
│ ├── CVS40_Brain_3D.txt
│ ├── CVS50_Brain_3D.txt
│ ├── CVS60_Brain_3D.txt
│ ├── CVS70_Brain_3D.txt
│ ├── CVS80_Brain_3D.txt
│ └── CVS90_Brain_3D.txt
├── Panel S8C
│ ├── CVS1_Flank_2D.txt
│ ├── CVS20_Flank_2D.txt
│ ├── CVS30_Flank_2D.txt
│ ├── CVS40_Flank_2D.txt
│ ├── CVS50_Flank_2D.txt
│ ├── CVS60_Flank_2D.txt
│ ├── CVS70_Flank_2D.txt
│ ├── CVS80_Flank_2D.txt
│ └── CVS90_Flank_2D.txt
├── Panel S8D
│ ├── CVS1_Flank_3D.txt
│ ├── CVS20_Flank_3D.txt
│ ├── CVS30_Flank_3D.txt
│ ├── CVS40_Flank_3D.txt
│ ├── CVS50_Flank_3D.txt
│ ├── CVS60_Flank_3D.txt
│ ├── CVS70_Flank_3D.txt
│ ├── CVS80_Flank_3D.txt
│ └── CVS90_Flank_3D.txt
├── Panel S8E
│ ├── CVS10_Lung_2D.txt
│ ├── CVS20_Lung_2D.txt
│ ├── CVS30_Lung_2D.txt
│ ├── CVS40_Lung_2D.txt
│ ├── CVS50_Lung_2D.txt
│ ├── CVS60_Lung_2D.txt
│ ├── CVS70_Lung_2D.txt
│ ├── CVS80_Lung_2D.txt
│ └── CVS90_Lung_2D.txt
└── Panel S8F
├── CVS10_Lung_3D.txt
├── CVS20_Lung_3D.txt
├── CVS30_Lung_3D.txt
├── CVS40_Lung_3D.txt
├── CVS50_Lung_3D.txt
├── CVS60_Lung_3D.txt
├── CVS70_Lung_3D.txt
├── CVS80_Lung_3D.txt
└── CVS90_Lung_3D.txt
All the files from Figure S7 and S8 (Method_Dataset_Modality.txt, Method = CV % / CVS % with % being the percentage value, Dataset = Brain/Flank/Brain, Modality = 2D/3D) contain columns:
Nominal Iron Mass [ug]: Iron mass put into the Brain/Flank/Lung ROI.
Iron Mass [ug]: Iron mass quantified from 2D/3D with the CV % / CVS % segmentation.
Iron Mass Error [ug]: Error propagated from the reference sample fits.
