Innate metabolic imaging of cellular systems
Described herein are systems and methods for image-based (e.g., MRI-based) spatial and temporal mapping of macrophages and other cell types, without the need for image contrast agents. These systems and methods are particularly useful for imaging macrophages because they naturally store metabolites, such as iron. Alternatively, the systems and methods described herein can be used where contrast agents are administered, rather than looking only at endogenous metabolite deposits.
1. A method of mapping one or more cell types in an image, the method comprising:
(a) accessing an image of a subject;
(b) generating at least one of a two-dimensional (2D) parametric map or a three-dimensional (3D) parametric map from the image, wherein the at least one of the 2D parametric map or the 3D parametric map includes a metabolite;
(c) generating at least one of a spatial 2D map of pixels or a spatial 3D map of voxels within one or more discrete metabolite concentration ranges using the at least one of the 2D parametric map or the 3D parametric map in step (b), thereby identifying each of one or more regions of the image with a corresponding metabolite concentration range; and
(d) for each of the one or more regions of the image, identifying a particular cell type according to its corresponding metabolite concentration range.
2. The method of claim 1 , wherein the image comprises an MM image, a computational tomography (CT) image, a positron emission tomography (PET) image, a single-photon emission computed tomography (SPECT) image, an optical image, fluorescence image, an ultrasound image, and/or any combination thereof.
3. The method of claim 1 , wherein the image comprises an MM image.
4. The method of claim 1 , wherein the metabolite depicted in the at least one of the 2D spatial map or the 3D spatial map comprises a member selected from group consisting of iron, glucose, amino acids, nucleotides, vitamins, antioxidants, proteins, and lipids.
5. The method of claim 1 , wherein the metabolite depicted in the at least one of the 2D spatial map or the 3D spatial map comprises iron.
6. The method of claim 1 , wherein the image comprises an MRI image, and wherein the metabolite depicted in the at least one of the 2D spatial map or the 3D spatial map comprises iron.
7. The method of claim 1 , wherein the at least one of the 2D parametric map or the 3D parametric map is a visual representation of an indirectly measured parameter that is mapped as a function of a directly recorded imaging parameter.
8. The method of claim 7 , wherein the indirectly measured parameter is at least one of a concentration, a perfusion rate, and a diffusion coefficient, and wherein the directly measured imaging parameter is at least one of a signal contrast level or a signal relaxation time.
9. The method of claim 7 , wherein the at least one of the 2D parametric map or the 3D parametric map comprises an iron(III) map, and wherein the concentration range is a range equivalent to or within endpoints of about 0 to about 0.3 mg/g iron at 7 T.
10. The method of claim 1 , wherein the one or more cell types comprise macrophages.
11. The method of claim 1 , wherein the one or more cell types comprise tumor-associated macrophages (TAMs).
12. The method of claim 1 , wherein the one or more cell types comprise cancer cells and wherein the cancer cells include at least one of adrenocortical carcinoma cells, astrocytoma cells, basal cell carcinoma cells, carcinoid cells, cardiac cells, cholangiocarcinoma cells, chordoma cells, chronic myeloproliferative neoplasms cells, craniopharyngioma cells, ductal carcinoma in situ, ependymoma cells, intraocular melanoma cells, gastrointestinal carcinoid tumor cells, gastrointestinal stromal tumor (GIST) cells, gestational trophoblastic disease cells, glioma, histiocytosis cells, leukemia cells, merkel cell carcinoma cells, mesothelioma cells, myeloma cells, myelodysplastic syndrome cells, papillomatosis cells, paraganglioma cells, pheochromacytoma cells, pleuropulmonary blastoma cells, retinoblastoma cells, sarcoma cells, or Wilms' tumor cells.
13. The method of claim 1 , wherein step (b) comprises generating the at least one of the 2D parametric map or the 3D parametric map from the image using a calibration curve.
14. The method of claim 1 , wherein step (b) comprises generating the at least one of the 2D parametric map or the 3D parametric map from the image using a regression analysis, and wherein the metabolite is iron R 2 *=1/T 2 * vs. mg iron(III) g −1 .
15. The method of claim 1 , wherein the at least one of the 2D parametric map or the 3D parametric map covers a discrete quantifiable concentration range at a given magnetic field.
16. The method of claim 15 , wherein the at least one of the 2D parametric map or the 3D parametric map comprises an iron(III) map, and wherein the concentration range is a range having at least 0.2 or at least 0.3 mg/g iron as an upper bound.
17. The method of claim 15 , wherein the at least one of the 2D parametric map or the 3D parametric map is an iron(III) map, and wherein the concentration range spans a range at least about 0.1 mg/g iron, at least about 0.15 mg/g iron, or at least about 0.2 mg/g iron.
18. The method of claim 15 , wherein the given magnetic field affects the discrete quantifiable concentration range, and wherein the specific iron concentration range that is utilized is field strength dependent and varies with magnetic field.
19. The method of claim 15 , wherein the at least one of the 2D parametric map or the 3D parametric map covers multiple discrete quantifiable ranges including a high range and a low range, and wherein the range is defined by the median of the range at a given magnetic field strength.
20. The method of claim 1 , where the metabolite being mapped is an endogenous metabolite and wherein no metabolite-containing contrast agent has been administered to the subject.
21. The method of claim 1 , wherein the step of generating the at least one of the 2D spatial map or the 3D spatial map within one or more discrete metabolite concentration ranges using the at least one of the 2D parametric map or the 3D parametric map in step (b) is conducted by performing histogram-based thresholding of the at least one of the 2D parametric map or the 3D parametric map.
22. The method of claim 1 , further comprising quantifying an extent of infiltration of tumor-associated macrophages (TAMs) by mapping regions of the image with high metabolite concentration as a function of percent infiltration of a tumor.
23. The method of claim 22 , wherein the metabolite comprises iron, and the high iron concentration is in a range from about 0.1 to about 0.2 mg/g iron or from about 0.15 to about 0.16 mg/g iron.
24. The method of claim 23 , wherein the metabolite concentration is quantified by performing concentric rake sampling.
25. The method of claim 1 , further comprising:
(e) performing steps (a) to (d) for each of a plurality of images obtained from the subject at different times to monitor progression of macrophages in the subject.
26. The method of claim 25 , comprising monitoring immune response to cancer therapy.
27. A system for mapping one or more cell types in an image, the system comprising:
a processor; and
a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:
(a) access an image of a subject;
(b) generate at least one of a two-dimensional (2D) parametric map or a three-dimensional (3D) parametric map from the image, wherein the at least one of the 2D parametric map or the 3D parametric map includes from the image;
(c) generate at least one of a spatial 2D map of pixels or a spatial 3D map of voxels within one or more discrete metabolite concentration ranges using the map in step (b), thereby identifying each of one or more regions of the image with a corresponding metabolic concentration range; and
(d) for each of the one or more regions of the MM image, identify a particular cell type according to its corresponding metabolite concentration range.