Tumor sphere quantification plays an important role in cancer research and drugs screening. Even though the number and size of tumor spheres can be found manually, this process is time-consuming, prone to making errors, and may not be viable when the number of images is very large. This manuscript presents a method for automated quantification of spheres with a novel segmentation technique. The segmentation method relies on initial watershed algorithm which detects the minima of the distance transform and finds a tumor sphere for each minimum. Due to the irregular edges of tumor spheres, the distance transform matrix has often more number of minima than the true number of spheres. This leads to the over segmentation problem. The proposed approach uses the smoothed form of the distance transform to effectively eliminate superfluous minima and then seeds the watershed algorithm with the remaining minima. The proposed method was validated over pancreatic tumor spheres images achieving high efficiency for tumor spheres quantification.
Purpose: The energy-yielding mitochondrial Krebs cycle has been shown in many cancers and other diseases to be inhibited or mutated. In most cells, the Krebs cycle with oxidative phosphorylation generates approximately 90% of the adenosine triphosphate in the cell. We designed and hyperpolarized carbon-13 labeled succinate (SUC) and its derivative diethyl succinate (DES) to interrogate the Krebs cycle in real-time in cancer animal models.
Procedures: Using Parahydrogen Induced Polarization (PHIP), we generated hyperpolarized SUC and DES by hydrogenating their respective fumarate precursors. DES and SUC metabolism was studied in five cancer allograft animal models: breast (4T1), Renal Cell Carcinoma (RENCA), colon (CT26), lymphoma NSO, and lymphoma A20.
Results: The extent of hyperpolarization was 8 ± 2% for SUC and 2.1 ± 0.6% for DES. The metabolism of DES and SUC in the Krebs cycle could be followed in animals 5 s after tail vein injection. The biodistribution of the compounds was observed using 13C FISP imaging. We observed significant differences in uptake and conversion of both compounds in different cell types both in vivo and in vitro.
Conclusion: With hyperpolarized DES and SUC, we are able to meet many of the requirements for a useable in vivo metabolic imaging compound - high polarization, relatively long T1 values, low toxicity and high water solubility. However, succinate and its derivative DES are metabolized robustly by RENCA but not by the other cancer models. Our results underscore the heterogeneity of cancer cells and the role cellular uptake plays in hyperpolarized metabolic spectroscopy.
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