Maximum Standardized Uptake Value of (99m)Tc Hydroxymethylene Diphosphonate SPECT/CT for the Evaluation of Temporomandibular Joint Disorder.

Purpose To evaluate the diagnostic accuracy of the quantitative parameter standardized uptake value (SUV) at single photon emission computed tomography (SPECT)/computed tomography (CT) for the evaluation of temporomandibular joint (TMJ) disorder (TMD). Materials and Methods This study was approved by the institutional review board, and the need for informed consent was waived. Forty-four TMJs in 22 patients with TMD (five men and 17 women; mean age ± standard deviation, 30.0 years ± 12.1) were evaluated. The patients underwent planar bone scintigraphy and SPECT/CT 3-4 hours after injection of technetium 99m hydroxymethylene diphosphonate. The planar scintigraphy parameter of relative ratio (RR) and SPECT/CT parameters mean SUV (SUVmean) and maximum SUV (SUVmax) were compared for the visual assessment of TMD on planar scintigraphy images and for the presence of TMJ arthralgia. Group comparisons, receiver operating characteristic analysis, and Pearson correlation analysis were conducted. Results SUVmax gradually increased from normal (2.82 ± 0.73) to mild or moderately abnormal (3.56 ± 0.76, P < .05) and then to severely abnormal (4.86 ± 1.25, P < .05). However, RR and SUVmean did not vary significantly according to visual grade (P > .05). On the other hand, SUVmax was significantly greater in arthralgic TMJs (4.15 ± 1.11) than in nonarthralgic TMJs (2.97 ± 0.75, P < .001), as was SUVmean (1.63 ± 0.42 vs 1.30 ± 0.31, respectively; P = .005). However, there was no significant difference in RR (3.61 ± 0.57 vs 3.76 ± 0.68, P = .45). In receiver operating characteristic curve analyses for arthralgic TMJ, SUVmax had the greatest area under the curve (area of 0.815). Conclusion SUVmax derived from bone SPECT/CT may be useful for the evaluation of TMD. (©) RSNA, 2016 Online supplemental material is available for this article.

Voxel-Based Internal Dosimetry for 177Lu-Labeled Radiopharmaceutical Therapy Using Deep Residual Learning.

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 177Lu-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 177Lu-labeled radiopharmaceuticals.

Comparison of voxel S-value methods for personalized voxel-based dosimetry of 177 Lu-DOTATATE.

PURPOSE: Voxel-based dosimetry is potentially accurate than organ-based dosimetry because it considers the anatomical variations in each individual and the heterogeneous radioactivity distribution in each organ. Here, voxel-based dosimetry for 177 Lu-DOTATATE therapy was performed using single and multiple voxel S-value (VSV) methods and compared with Monte Carlo simulations. To verify these methods, we adopted sequential 177 Lu-DOTATATE single-photon emission computed tomography and X-ray computed tomography (SPECT/CT) dataset acquired from Sunway Medical Centre using the major vendor's SPECT/CT scanner (Siemens Symbia Intevo). METHODS: The administered activity of 177 Lu-DOTATATE was 7.99 ± 0.36 GBq. SPECT/CT images were acquired 0.5, 4, 24, and 48 h after injection in Sunway Medical Centre. For the multiple VSV method, VSV kernels of 177 Lu in media with various densities were generated by Geant4 Application for Emission Tomography (GATE) simulation first. The second step involved the convolution of the time-integrated activity map with each kernel to produce medium-specific dose maps. Third, each medium-specific dose map was masked using binary medium masks, which were generated from CT-based density maps. Finally, all masked dose maps were summed to generate the final dose map. VSV methods with four different VSV sets (1, 4, 10, and 20 VSVs) were compared. Voxel-wise density correction for the single VSV method was also performed. The absorbed doses in the kidneys, bone marrow, and tumors were analyzed, and the relative errors between the VSV and Monte Carlo simulation approaches were estimated. Organ-based dosimetry using Organ Level INternal Dose Assessment/EXponential Modeling (OLINDA/EXM) was also compared. RESULTS: The accuracy of the multiple VSV approach increased with the number of dose kernels. The average dose estimation errors of a single VSV with density correction and 20 VSVs were less than 6% in most cases, although organ-based dosimetry using OLINDA/EXM yielded an error of up to 123%. The advantages of the single VSV method with density correction and the 20 VSVs over organ-based dosimetry were most evident in bone marrow and bone-metastatic tumors with heterogeneous medium properties. CONCLUSION: The single VSV method with density correction and multiple VSV method with 20 dose kernels enabled fast and accurate radiation dose estimation. Accordingly, voxel-based dosimetry methods can be useful for managing administration activity and for investigating tumor dose responses to further increase the therapeutic efficacy of 177 Lu-DOTATATE.

Prognosis prediction of pancreatic cancer after curative intent surgery using imaging parameters derived from F-18 fluorodeoxyglucose positron emission tomography/computed tomography.

Imaging parameters including metabolic or textural parameters during F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) are being used for evaluation of malignancy. However, their utility for prognosis prediction has not been thoroughly investigated. Here, we evaluated the prognosis prediction ability of imaging parameters from preoperative FDGPET/CT in operable pancreatic cancer patients.Sixty pancreatic cancer patients (male:female = 36:24, age = 67.2 ±â€Š10.5 years) who had undergone FDGPET/CT before the curative intent surgery were enrolled. Clinico-pathologic parameters, metabolic parameters from FDGPET/CT; maximal standard uptake value (SUVmax), glucose-incorporated SUVmax (GI-SUVmax), metabolic tumor volume, total-lesion glycolysis, and 53 textural parameters derived from imaging analysis software (MaZda version 4.6) were compared with overall survival.All the patients underwent curative resection. Mean and standard deviation of overall follow-up duration was 16.12 ±â€Š9.81months. Among them, 39 patients had died at 13.46 ±â€Š8.82 months after operation, whereas 21 patients survived with the follow-up duration of 18.56 ±â€Š9.97 months. In the univariate analysis, Tumor diameter ≥4 cm (P = .003), Preoperative Carbohydrate antigen 19-9 ≥37 U/mL (P = .034), number of metastatic lymph node (P = .048) and GI-SUVmax (P = .004) were significant parameters for decreased overall survival. Among the textural parameters, kurtosis3D (P = .052), and skewness3D (P = .064) were potentially significant predictors in the univariate analysis. However, in multivariate analysis only GI-SUVmax (P = .026) and combined operation (P = .001) were significant independent predictors of overall survival.The current research result indicates that metabolic parameter (GI-SUVmax) from FDGPET/CT, and combined operation could predict the overall survival of surgically resected pancreatic cancer patients. Other metabolic or textural imaging parameters were not significant predictors for overall survival of localized pancreatic cancer.

Quantitative Single-Photon Emission Computed Tomography/Computed Tomography for Glomerular Filtration Rate Measurement.

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 volunteers was 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.