Journal of nuclear medicine : official publication, Society of Nuclear Medicine
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Prediction of postoperative pulmonary function in lung cancer patients before tumor resection is essential for patient selection for surgery and is conventionally done with a nonimaging segment counting method (SC) or 2-dimensional planar lung perfusion scintigraphy (PS). The purpose of this study was to compare quantitative analysis of PS to SPECT/CT and to estimate the accuracy of SC, PS, and SPECT/CT in predicting postoperative pulmonary function in patients undergoing lobectomy. Methods: Seventy-five non-small cell lung cancer patients planned for lobectomy were prospectively enrolled (68% male; average age, 68.1 ± 8 y). ⋯ Conclusion: Although lobar quantification parameters differed significantly between PS and SPECT/CT, no significant differences were found between the predicted postoperative lung function results derived from these methods and the actual postoperative results. The additional time and effort of SPECT/CT quantification may not have an added value in patient selection for surgery. SPECT/CT may be advantageous in patients planned for right lobectomy, but further research is warranted.
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68Ga-DOTATOC PET/MRI combines the advantages of PET in the acquisition of metabolic-functional information with the high soft-tissue contrast of MRI. SUVs in tumors have been suggested to be a measure of somatostatin receptor expression. A challenge with receptor ligands is that the distribution volume is confined to tissues with tracer uptake, potentially limiting SUV quantification. ⋯ On the basis of a threshold ratio of 0.03, tumors could be classified as grade 2 with a sensitivity of 86% and a specificity of 100%. SUV and functional ADCs, as well as arterial contrast enhancement parameters, showed nonsignificant and mostly negligible correlations. Conclusion: Because receptor density and tumor cellularity appear to be independent, potentially complementary phenomena, the combined ratio of PET/MRI and SUVmean/ADCmin may be used as a novel biomarker allowing differentiation between grade 1 and grade 2 GEP NETs.