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Purpose@#In this study, we propose a deep learning (DL)–based voxel-based dosimetry method in which dose maps acquired using the multiple voxel S-value (VSV) approach were used for residual learning. @*Methods@#Twenty-two SPECT/CT datasets from seven patients who underwent 177 Lu-DOTATATE treatment were used in this study. The dose maps generated from Monte Carlo (MC) simulations were used as the reference approach and target images for network training. The multiple VSV approach was used for residual learning and compared with dose maps generated from deep learning. The conventional 3D U-Net network was modified for residual learning. The absorbed doses in the organs were calculated as the mass-weighted average of the volume of interest (VOI). @*Results@#The DL approach provided a slightly more accurate estimation than the multiple-VSV approach, but the results were not statistically significant. The single-VSV approach yielded a relatively inaccurate estimation. No significant difference was noted between the multiple VSV and DL approach on the dose maps. However, this difference was prominent in the error maps. The multiple VSV and DL approach showed a similar correlation. In contrast, the multiple VSV approach underestimated doses in the low-dose range, but it accounted for the underestimation when the DL approach was applied. @*Conclusion@#Dose estimation using the deep learning–based approach was approximately equal to that in the MC simulation. Accordingly, the proposed deep learning network is useful for accurate and fast dosimetry after radiation therapy using 177 Lu-labeled radiopharmaceuticals.
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PURPOSE: We propose a quantitative Tc-99m diethylenetriaminepentaacetic acid (DTPA) single-photon emission computed tomography/computed tomography (SPECT/CT) for glomerular filtration rate (GFR) measurement.METHODS: Quantitative SPECT/CT data obtained at 2–3 min post-Tc-99m DTPA injection (370 MBq) were used to determine % injected doses (%IDs) for individual kidneys. The reproducibility of %ID measurement was tested and compared with planar scintigraphy. Cr-51 ethylenediaminetetraacetic acid (EDTA) GFR was used as reference standard. Nine young volunteers, representing normal GFR, and ten older volunteers, reflecting impaired GFR, were enrolled. The established GFR equation derived from these volunteerswas applied to 19 renal tumor patients post-partial nephrectomy.RESULTS: At 2–3 min, %ID was most reproducible with the highest intraclass correlation (ICC) (0.9379) and lowest % coefficient of variation (CV) (6.5259%), which were more reliable than the ICC (0.9368) and %CV (6.7689%) of planar scintigraphy. Cr-51 EDTA GFR (93.16 ± 24.81 ml/min) correlated significantly with %ID (7.66 ± 2.15%, r = 0.7906, p = 0.0001), yielding an equation: Cr-51 EDTA GFR (ml/min) = (%ID × 9.1462) + 23.0653. This equation revealed significant decreases in total and nephrectomized kidney GFR (p = 0.0012 and p < 0.0001, respectively) from preoperative to 3-month postoperative measurements.CONCLUSIONS: Quantitative Tc-99m DTPA SPECT/CT produces reliable and clinically applicable %ID estimates that translate to the GFR of individual kidneys.