Background <p>Chronic limb- threatening ischemia (CLTI) is a serious condition that can lead to amputation, and in some cases, it can be associated with mortality. Current clinical evaluation methods have several limitations. Therefore, new methods to assess CLTI are needed to better understand and measure underlying causes and functionality, and hence potentially improve the treatment. In this study, we use dynamic <sup>18</sup>F-FAZA PET-imaging as a method of measuring hypoxia as a marker associated with CLTI, on twelve patients identified with CLTI who underwent <sup>18</sup>F-FAZA PET-MR imaging.</p> Results <p>The kinetic modelling goodness-of-fit metrics using AIF from independent limb with the irreversible-2TC3K model distinguished between index and contralateral limbs better than the reversable-2TC4K model. The Spearman correlation coefficients between the standardized uptake value (SUV) SUV-to-SUV<sub>med</sub> ratio and the perfusion parameter, <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13550_2025_1243_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="22" /> </InlineMediaObject> <EquationSource Format="TEX">\(\:{K}_{1}\)</EquationSource> </InlineEquation>, was <i>r</i><sub><i>s</i></sub> = -0.07 for index and <i>r</i><sub><i>s</i></sub> = 0.22 for contralateral limbs. For the SUV-to-SUV<sub>med</sub> ratio correlation with diffusion parameter, <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13550_2025_1243_Article_IEq2.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="18" /> </InlineMediaObject> <EquationSource Format="TEX">\(\:{\:k}_{3}\)</EquationSource> </InlineEquation>, it is found to be negative for both index (<i>r</i><sub><i>s</i></sub> = -0.16) and contralateral (<i>r</i><sub><i>s</i></sub> = -0.11).</p> Conclusions <p>The kinetic modelling of <sup>18</sup>F-FAZA dynamic PET-MR was able to differentiate between index and contralateral limbs in CLTI patients, and the diffusion metric from the kinetic modelling can potentially be used as a metric to measure hypoxia in CLTI.</p> Trial registration <p>ClinicalTrials.gov, NCT04054609. Registered 20,190,611, https//clinicaltrials.gov/study/NCT04054609.</p>

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Measuring hypoxia in chronic limb-threatening ischemia using 18F-FAZA kinetic modelling – a pilot study

  • Adam Farag,
  • Andres Kohan,
  • Tetsuro Sekine,
  • Seyed Ali Mirshahvalad,
  • Ur Metser,
  • Sebastian Mafeld,
  • Kongteng Tan,
  • Patrick Veit-Haibach

摘要

Background

Chronic limb- threatening ischemia (CLTI) is a serious condition that can lead to amputation, and in some cases, it can be associated with mortality. Current clinical evaluation methods have several limitations. Therefore, new methods to assess CLTI are needed to better understand and measure underlying causes and functionality, and hence potentially improve the treatment. In this study, we use dynamic 18F-FAZA PET-imaging as a method of measuring hypoxia as a marker associated with CLTI, on twelve patients identified with CLTI who underwent 18F-FAZA PET-MR imaging.

Results

The kinetic modelling goodness-of-fit metrics using AIF from independent limb with the irreversible-2TC3K model distinguished between index and contralateral limbs better than the reversable-2TC4K model. The Spearman correlation coefficients between the standardized uptake value (SUV) SUV-to-SUVmed ratio and the perfusion parameter, \(\:{K}_{1}\) , was rs = -0.07 for index and rs = 0.22 for contralateral limbs. For the SUV-to-SUVmed ratio correlation with diffusion parameter, \(\:{\:k}_{3}\) , it is found to be negative for both index (rs = -0.16) and contralateral (rs = -0.11).

Conclusions

The kinetic modelling of 18F-FAZA dynamic PET-MR was able to differentiate between index and contralateral limbs in CLTI patients, and the diffusion metric from the kinetic modelling can potentially be used as a metric to measure hypoxia in CLTI.

Trial registration

ClinicalTrials.gov, NCT04054609. Registered 20,190,611, https//clinicaltrials.gov/study/NCT04054609.