Comparison of Whole-Body Dosimetry Measurements in 131I Therapy Using Ceiling-Mounted Geiger-Müller Detectors and γ-Camera Scans: An Agreement Analysis.

Background: In 131I therapies internal dosimetry is crucial for determining the mean absorbed dose to organs at risk, particularly the bone marrow, which has a dose constraint of 2 Gy. Traditionally, multicompartmental models have been used for bone marrow dosimetry, necessitating whole-body absorbed-dose assessments. However, noninvasive techniques, such as γ-camera scans or ceiling-mounted Geiger-Müller (GM) counters, can estimate the aforementioned. This study was aimed to evaluate the agreement between whole-body mean absorbed dose using γ-camera scans and ceiling-mounted GM in patients with thyroid carcinoma undergoing 131I therapy. Methods: This study included 31 patients with thyroid cancer who were treated with 131I. The whole-body time-integrated activity (TIA) and mean absorbed dose were estimated using the elimination curves obtained with γ-camera scans and ceiling-mounted GM. In addition, statistical analysis was performed on the data to determine the Coefficient Correlation Coefficient and the Bland-Altman limits of agreement for both parameters, as well as for the elimination curves' effective half-life. Results: The study revealed correlations of 0.562 and 0.586 between whole-body TIA and mean absorbed dose, respectively. The Bland-Altman limits of agreement were found to be below -3.75% and within 12.75% of the bone marrow dose constraint of 2 Gy. The nonparametric evaluation revealed that whole-body TIA and mean absorbed dose medians from GM were lower than those from γ-camera scans (p < 0.001). Effective half-life estimation mean was significantly lower in the GM than in the γ-camera of 13 and 23 h. Conclusions: Although GM calculates the whole-body absorbed dose with margins of error within clinical acceptance, underestimation of the effective half-life makes it an unacceptable substitute method for γ-cameras in clinical practice. Further research should be conducted to evaluate single-point GM measurement substitutions in time-activity curves.

Feasibility of Thorium-227/Radium-223 Gamma-Camera Imaging During Radionuclide Therapy.

Thorium-227 (227Th) is a long-lived (T1/2 = 18.7 d) α-emitter that has emerged as candidate for radioimmunotherapy. Imaging of patients treated with thorium-227 conjugates is challenging due to the low activity administered and to photon emissions with low yields. In addition, the radioactive daughter radium-223 (223Ra) have photon emissions in the same energy range as 227Th. The long half-life of 223Ra (T1/2 = 11.4 d) and the possibility of redistribution motivates efforts to separate 227Th and 223Ra. The aim of this study was to investigate the feasibility of imaging of patients treated with 227Th-labeled-monoclonal antibody (mAb) and to determine acquisition and image processing parameters to enable discrimination between 227Th and 223Ra. Imaging was performed with a GE Discovery 670 NM/CT γ-camera. Radionuclide separation with different energy windows (EW) and collimators was studied in images of vials with either 227Th or 223Ra. Phantom acquisitions with clinically relevant activities were performed to assess image quality and the usefulness of background subtraction and spatial filtering. Two patients treated with 227Th-labeled-mAb were imaged. Imaging of vials showed that 223Ra can be distinguished from 227Th using multiple energy windows. Medium- and high-energy collimators showed similar performance of sensitivity and spatial resolution, whereas the low-energy collimator had higher sensitivity but poor resolution due to collimator penetration. Visually, the image quality was improved with background subtraction and spatial filtering. The patient images exhibited the expected image quality and a possibility to separate 227Th and 223Ra. γ-Camera imaging of patients treated with 227Th-mAb is feasible and 223Ra can be distinguished from 227Th. Image quality is substantially improved using background subtraction and a spatial smoothing filter. Acquisition settings recommended for planar images are: high-energy general purpose or medium-energy general purpose collimator, 40 min acquisition time and energy windows: (1) 70-100 keV (227Th and 223Ra); (2) 215-260 keV (227Th); (3) 260-290 keV (223Ra); (4) 350-420 keV (223Ra).

Improved nuclear medicine uniformity assessment with noise texture analysis.

UNLABELLED: Because γ cameras are generally susceptible to environmental conditions and system vulnerabilities, they require routine evaluation of uniformity performance. The metrics for such evaluations are commonly pixel value-based. Although these metrics are typically successful at identifying regional nonuniformities, they often do not adequately reflect subtle periodic structures; therefore, additional visual inspections are required. The goal of this project was to develop, test, and validate a new uniformity analysis metric capable of accurately identifying structures and patterns present in nuclear medicine flood-field uniformity images. METHODS: A new uniformity assessment metric, termed the structured noise index (SNI), was based on the 2-dimensional noise power spectrum (NPS). The contribution of quantum noise was subtracted from the NPS of a flood-field uniformity image, resulting in an NPS representing image artifacts. A visual response filter function was then applied to both the original NPS and the artifact NPS. A single quantitative score was calculated on the basis of the magnitude of the artifact. To verify the validity of the SNI, an observer study was performed with 5 expert nuclear medicine physicists. The correlation between the SNI and the visual score was assessed with Spearman rank correlation analysis. The SNI was also compared with pixel value-based assessment metrics modeled on the National Electrical Manufacturers Association standard for integral uniformity in both the useful field of view (UFOV) and the central field of view (CFOV). RESULTS: The SNI outperformed the pixel value-based metrics in terms of its correlation with the visual score (ρ values for the SNI, integral UFOV, and integral CFOV were 0.86, 0.59, and 0.58, respectively). The SNI had 100% sensitivity for identifying both structured and nonstructured nonuniformities; for the integral UFOV and CFOV metrics, the sensitivities were only 62% and 54%, respectively. The overall positive predictive value of the SNI was 87%; for the integral UFOV and CFOV metrics, the positive predictive values were only 67% and 50%, respectively. CONCLUSION: The SNI accurately identified both structured and nonstructured flood-field nonuniformities and correlated closely with expert visual assessment. Compared with traditional pixel value-based analysis, the SNI showed superior performance in terms of its correlation with visual perception. The SNI method is effective for detecting and quantifying visually apparent nonuniformities and may reduce the need for more subjective visual analyses.