From Phantoms to Patients: Improved Fusion and Voxel-Wise Analysis of Diffusion-Weighted Imaging and FDG-Positron Emission Tomography in Positron Emission Tomography/Magnetic Resonance Imaging for Combined Metabolic–Diffusivity Index (cDMI)
Hybrid positron emission tomography/magnetic resonance imaging (PET/MR) opens new possibilities in multimodal multiparametric (m2p) image analyses. But even the simultaneous acquisition of positron emission tomography (PET) and magnetic resonance imaging (MRI) does not guarantee perfect voxel-by-voxel co-registration due to organs and distortions, especially in diffusion-weighted imaging (DWI), which would be, however, crucial to derive biologically meaningful information. Thus, our aim was to optimize fusion and voxel-wise analyses of DWI and standardized uptake values (SUVs) using a novel software for m2p analyses. Using research software, we evaluated the precision of image co-registration and voxel-wise analyses including the rigid and elastic 3D registration of DWI and [18F]-Fluorodeoxyglucose (FDG)-PET from an integrated PET/MR system. We analyzed DWI distortions with a volume-preserving constraint in three different 3D-printed phantom models. A total of 12 PET/MR-DWI clinical datasets (bronchial carcinoma patients) were referenced to the T1 weighted-DIXON sequence. Back mapping of scatterplots and voxel-wise registration was performed and compared to the non-optimized datasets. Fusion was rated using a 5-point Likert scale. Using the 3D-elastic co-registration algorithm, geometric shapes were restored in phantom measurements; the measured ADC values did not change significantly (F = 1.12, p = 0.34). Reader assessment showed a significant improvement in fusion precision for DWI and morphological landmarks in the 3D-registered datasets (4.3 ± 0.2 vs. 4.6 ± 0.2, p = 0.009). Most pronounced differences were noted for the chest wall (p = 0.006), tumor (p = 0.007), and skin contour (p = 0.014). Co-registration increased the number of plausible ADC and SUV combinations by 25%. The volume-preserving elastic 3D registration of DWI significantly improved the precision of fusion with anatomical sequences in phantom and clinical datasets. The research software allowed for a voxel-wise analysis and visualization of [18F]FDG-PET/MR data as a “combined diffusivity–metabolic index” (cDMI). The clinical value of the optimized PET/MR biomarker can thus be tested in future PET/MR studies.
Authors
- Tobias Speidel (ORCID: https://orcid.org/0000-0002-7917-8332)
- Gerlinde Schmidtke-Schrezenmeier
- Wolfgang Thaiss (ORCID: https://orcid.org/0000-0002-0796-780X)
- Katharina Deininger
- Ralph Strecker (ORCID: https://orcid.org/0000-0002-8232-8952)
- Meinrad Beer (ORCID: https://orcid.org/0000-0001-7523-1979)
- B. Mühling
- Ambros J. Beer (ORCID: https://orcid.org/0000-0001-9042-7806)
- Catharina Silvia Lisson
- Volker Rasche (ORCID: https://orcid.org/0000-0001-8844-3583)
- Robert Grimm (ORCID: https://orcid.org/0000-0002-1233-8215)
- Gerhard Glatting (ORCID: https://orcid.org/0000-0001-7916-1576)
- Patrick Korf
- Jochen Steinacker (ORCID: https://orcid.org/0000-0002-8627-4779)
- Leonard Lauber
Institutions
- Universität Ulm (DE)
- Siemens Healthineers (Germany) (DE)
- University Hospital Ulm (DE)
Publication Details
- Journal
- Diagnostics
- Published
- 2024-08-16
- DOI
- https://doi.org/10.3390/diagnostics14161787
- Citations
- 1
- Primary Topic
- MRI in cancer diagnosis
- Type
- article
- Field-Weighted Citation Impact
- 0.40