Fanny Orlhac1, Benoit Thézé2, Michaël Soussan2,3, Raphaël Boisgard2, Irène Buvat2. 1. Imagerie Moléculaire In Vivo, INSERM, CEA, University Paris Sud, CNRS, Université Paris Saclay, CEA-Service Hospitalier Frédéric Joliot, Orsay, France; and orlhacf@gmail.com. 2. Imagerie Moléculaire In Vivo, INSERM, CEA, University Paris Sud, CNRS, Université Paris Saclay, CEA-Service Hospitalier Frédéric Joliot, Orsay, France; and. 3. Department of Nuclear Medicine, AP-HP, Avicenne Hospital, Bobigny, France.
Abstract
Characterizing tumor heterogeneity using texture indices derived from PET images has shown promise in predicting treatment response and patient survival in some types of cancer. Yet, the relationship between PET-derived texture indices, precise tracer distribution, and biologic heterogeneity needs to be clarified. We investigated this relationship using PET images, autoradiographic images, and histologic images. METHODS: Three mice bearing orthotopically implanted mammary tumors derived from transgenic MMTV-PyMT mice were scanned with 18F-FDG PET/CT. The tumors were then sliced, and the slices were imaged with autoradiography and stained with hematoxylin and eosin. Six texture indices derived from the PET images, autoradiographic images, and histologic images were compared for their ability to capture heterogeneity on different scales. RESULTS: The PET-derived indices correlated significantly with the autoradiography-derived ones (R = 0.57-0.85), but the values differed in magnitude. The histology-derived indices correlated poorly with the autoradiography- and PET-derived ones (R = 0.06-0.54). All indices were slightly to moderately influenced by the difference in voxel size and spatial resolution in the autoradiographic images. The autoradiography-derived indices differed significantly (P < 0.05) between regions with a high density of cells and regions with a low density and between regions with different spatial arrangements of cells. CONCLUSION: Heterogeneity derived in vivo from PET images accurately reflects the heterogeneity of tracer uptake derived ex vivo from autoradiographic images. Various tumor-cell densities and spatial cell distributions seen on histologic images can be distinguished using texture indices derived from autoradiographic images despite the difference in voxel size and spatial resolution. Yet, tumor texture derived from PET images only coarsely reflects the spatial distribution and density of tumor cells.
Characterizing tumor heterogeneity using texture indices derived from PET images has shown promise in predicting treatment response and patient survival in some types of cancer. Yet, the relationship between PET-derived texture indices, precise tracer distribution, and biologic heterogeneity needs to be clarified. We investigated this relationship using PET images, autoradiographic images, and histologic images. METHODS: Three mice bearing orthotopically implanted mammary tumors derived from transgenic MMTV-PyMT mice were scanned with 18F-FDG PET/CT. The tumors were then sliced, and the slices were imaged with autoradiography and stained with hematoxylin and eosin. Six texture indices derived from the PET images, autoradiographic images, and histologic images were compared for their ability to capture heterogeneity on different scales. RESULTS: The PET-derived indices correlated significantly with the autoradiography-derived ones (R = 0.57-0.85), but the values differed in magnitude. The histology-derived indices correlated poorly with the autoradiography- and PET-derived ones (R = 0.06-0.54). All indices were slightly to moderately influenced by the difference in voxel size and spatial resolution in the autoradiographic images. The autoradiography-derived indices differed significantly (P < 0.05) between regions with a high density of cells and regions with a low density and between regions with different spatial arrangements of cells. CONCLUSION: Heterogeneity derived in vivo from PET images accurately reflects the heterogeneity of tracer uptake derived ex vivo from autoradiographic images. Various tumor-cell densities and spatial cell distributions seen on histologic images can be distinguished using texture indices derived from autoradiographic images despite the difference in voxel size and spatial resolution. Yet, tumor texture derived from PET images only coarsely reflects the spatial distribution and density of tumor cells.
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