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Research ArticleImaging

Acquisition Duration Optimization Using Visual Grading Regression in [68Ga]FAPI-46 PET Imaging of Oncologic Patients

Ted Nilsson, Pawel Rasinski, Örjan Smedby, Siri af Burén, Ernesto Sparrelid, J. Matthias Löhr, Thuy A. Tran, August Blomgren, Antonios Tzortzakakis, Rimma Axelsson and Maria Holstensson
Journal of Nuclear Medicine Technology April 2024, jnmt.123.267156; DOI: https://doi.org/10.2967/jnmt.123.267156
Ted Nilsson
1Department of Clinical Science, Intervention, and Technology, Karolinska Institutet, Stockholm, Sweden;
2Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Huddinge, Sweden;
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Pawel Rasinski
1Department of Clinical Science, Intervention, and Technology, Karolinska Institutet, Stockholm, Sweden;
2Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Huddinge, Sweden;
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Örjan Smedby
3Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Huddinge, Sweden;
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Siri af Burén
1Department of Clinical Science, Intervention, and Technology, Karolinska Institutet, Stockholm, Sweden;
2Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Huddinge, Sweden;
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Ernesto Sparrelid
1Department of Clinical Science, Intervention, and Technology, Karolinska Institutet, Stockholm, Sweden;
4Department of Upper Gastrointestinal Diseases, Karolinska University Hospital, Huddinge, Sweden;
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J. Matthias Löhr
1Department of Clinical Science, Intervention, and Technology, Karolinska Institutet, Stockholm, Sweden;
4Department of Upper Gastrointestinal Diseases, Karolinska University Hospital, Huddinge, Sweden;
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Thuy A. Tran
5Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden;
6Department of Radiopharmacy, Karolinska University Hospital, Stockholm, Sweden; and
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August Blomgren
2Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Huddinge, Sweden;
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Antonios Tzortzakakis
1Department of Clinical Science, Intervention, and Technology, Karolinska Institutet, Stockholm, Sweden;
2Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Huddinge, Sweden;
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Rimma Axelsson
2Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Huddinge, Sweden;
7Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
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Maria Holstensson
1Department of Clinical Science, Intervention, and Technology, Karolinska Institutet, Stockholm, Sweden;
2Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Huddinge, Sweden;
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  • FIGURE 1.
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    FIGURE 1.

    Maximum-intensity projection and axial PET images with corresponding contrast-enhanced CT and fused images presenting image quality in relation to acquisition duration of [68Ga]FAPI-46 imaging. Reference line (blue) for axial images is presented on maximum-intensity projection images. Arrows indicate interventricular septum of heart (image quality criterion B). CECT = contrast-enhanced CT; MIP = maximum-intensity projection.

  • FIGURE 2.
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    FIGURE 2.

    Results from scoring of criteria A–D presented with histogram for each camera, each rater, and each acquisition duration.

  • FIGURE 3.
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    FIGURE 3.

    Box plots of differences in SUVmax and SUVmean for 1, 2, and 3 min/bed position relative to 4 min/bed position. Asterisk represents outlier plotted as individual point.

  • FIGURE 4.
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    FIGURE 4.

    Box plots of LBR relative to 4 min/bed position using background liver, aorta, and musculature. Asterisks represent outliers plotted as individual points.

  • FIGURE 5.
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    FIGURE 5.

    Box plots of COV measured in background liver, aorta, and musculature at 1, 2, 3, and 4 min/bed position. Asterisks represent outliers plotted as individual points.

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    TABLE 1.

    Image Quality Criteria

    CriterionDefinition
    AIntercostal spaces are distinguishable from ribs, and structures such as costochondral cartilage and sternum are clearly discernible and distinct
    BInterventricular septum of heart is clearly discernible and distinct
    CNoise level does not disrupt evaluation
    DOverall image quality is good enough to make clinical diagnosis
    • View popup
    TABLE 2.

    Patient Characteristics

    Patient no.SexBody weight (kg)Age (y)BMIInjected activity (MBq)Activity by body weight (MBq/kg)CameraHistologic diagnosisSUVmaxSUVmeanLBRmax, bloodLesion volume (cm3)
    1F578522213.23.71PDAC23.814.220.610
    2F627220248.84.01PDAC25.013.019.341
    3F684928257.13.81PDAC18.412.016.14
    4M648322239.83.71PDAC15.48.110.614
    5M725723268.33.72PanIN3.73.02.81
    6M767425261.23.42PDAC18.912.410.621
    7M826525292.13.62PDAC15.68.012.111
    8M776924265.53.41PanIN1.10.71.14
    9M656621218.23.41IPMN5.32.95.210
    10F787924285.33.72PDAC9.96.37.48
    • BMI = body mass index; LBRmax,blood = SUVmax divided by background measurement in aorta; PDAC = pancreatic ductal adenocarcinoma; PanIN = pancreatic intraepithelial neoplasia; IPMN = intraductal papillary mucinous neoplasm.

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    TABLE 3.

    Analysis of Image Quality Scoring Using Visual Grading Regression

    Criterion ACriterion BCriterion CCriterion D
    ConditionRegression coefficientPRegression coefficientPRegression coefficientPRegression coefficientP
    1 min/bed−8.12<0.0001−7.19<0.0001−8.89<0.0001−6.61<0.0001
    2 min/bed−4.58<0.0001−3.99<0.0001−4.95<0.0001−3.770.0001
    3 min/bed−2.630.0022−1.360.0419−2.710.0007−1.020.2881
    4 min/bed————————
    Camera 2−0.350.82841.970.04502.040.01312.940.0005
    Camera 1————————
    Rater 23.30<0.00013.20<0.00011.940.00100.690.2495
    Rater 1————————
    • Reference categories are 4 min/bed, camera 1, and rater 1.

    • View popup
    TABLE 4.

    Comparison of SUVmax, SUVmean, and COV Measurements Using Paired Wilcoxon Signed-Rank Test

    ParameterMeasurementzP
    Mean SUVmax
     1 min/bed14.92−1.99<0.05
     2 min/bed13.98−1.480.14
     3 min/bed13.79−1.120.26
     4 min/bed13.71——
    Mean SUVmean
     1 min/bed4.64−1.220.22
     2 min/bed4.77−1.790.07
     3 min/bed4.90−1.130.26
     4 min/bed4.78——
    Mean liver COV
     1 min/bed0.21−2.81<0.01
     2 min/bed0.15−2.81<0.01
     3 min/bed0.14−2.70<0.01
     4 min/bed0.11——
    Mean aorta COV
     1 min/bed0.19−2.81<0.01
     2 min/bed0.14−2.81<0.01
     3 min/bed0.12−2.26<0.05
     4 min/bed0.10——
    Mean muscle COV
     1 min/bed0.23−2.81<0.01
     2 min/bed0.18−2.68<0.01
     3 min/bed0.16−2.23<0.05
     4 min/bed0.15——

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Journal of Nuclear Medicine Technology: 53 (1)
Journal of Nuclear Medicine Technology
Vol. 53, Issue 1
March 1, 2025
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Acquisition Duration Optimization Using Visual Grading Regression in [68Ga]FAPI-46 PET Imaging of Oncologic Patients
Ted Nilsson, Pawel Rasinski, Örjan Smedby, Siri af Burén, Ernesto Sparrelid, J. Matthias Löhr, Thuy A. Tran, August Blomgren, Antonios Tzortzakakis, Rimma Axelsson, Maria Holstensson
Journal of Nuclear Medicine Technology Apr 2024, jnmt.123.267156; DOI: 10.2967/jnmt.123.267156
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Keywords

  • PET
  • fibroblast activation protein
  • [68Ga]FAPI-46
  • pancreas
  • acquisition duration
  • visual grading
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Acquisition Duration Optimization Using Visual Grading Regression in [68Ga]FAPI-46 PET Imaging of Oncologic Patients
Ted Nilsson, Pawel Rasinski, Örjan Smedby, Siri af Burén, Ernesto Sparrelid, J. Matthias Löhr, Thuy A. Tran, August Blomgren, Antonios Tzortzakakis, Rimma Axelsson, Maria Holstensson
Journal of Nuclear Medicine Technology Apr 2024, jnmt.123.267156; DOI: 10.2967/jnmt.123.267156

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