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Background: Yttrium‐90 (90Y) positron emission tomography (PET)/computed tomography (CT) imaging is increasingly being used to perform tumor (T) and normal liver (NL) voxel dosimetry after 90Y‐radioembolization (90Y‐RE). Yet, the accuracy of in vivo 90Y‐PET/CT imaging, subject to motion blur and co‐registration inaccuracies, and 90Y‐PET/CT dose quantification, subject to availability of different voxel dosimetry algorithms, are not well understood. Purpose: The purpose of this study was to investigate the accuracy of 90Y‐PET/CT‐based activity estimates following 90Y‐RE and characterize differences between 90Y‐PET/CT‐based voxel dosimetry algorithms. Methods: Thirty‐five patients underwent 90Y‐PET/CT imaging after 90Y‐RE with TheraSphere. The net administered 90Y activity (Aadmin) was determined using a dose calibrator and pre‐ and post‐procedure exposure rate measurements. The summation of image‐based activity (Aimage) was extracted from perfused volume (PV) and 3D‐isotropically 2‐cm expanded PV contour (PV+2 cm). Absorbed doses were calculated using voxel S‐value (VSV), local deposition method (LDM), and LDM with known activity (LDMKA) dosimetry algorithms. Linear regression and Bland‐Altman analysis quantified the relationship between Aimage and Aadmin and between mean dose estimates (DLDM, DVSV, DLDM‐KA) for PV, T, and perfused NL volumes. Results: While Aadmin and Aimage in PV were highly correlated (R2 > 0.95), the mean bias ± standard error (SE) and (95% limits of agreement, LOA) was significantly non‐zero with −22.7 ± 4.7% (± 28.4%). In PV+2 cm, the mean bias ± SE (± LOA) decreased to 1.3 ± 3.4% (± 18.0%) consistent with zero mean error. DLDM and DVSV were highly correlated (R2 > 0.99) for all volumes of interest (VOIs) and the mean bias ± SE (± LOA) was 2.2 ± 0.2% (± 1.0%), 0.7 ± 0.4% (± 2.8%), and 3.2 ± 0.5% (± 2.8%) for PV, T, and NL, respectively. DLDM‐KA and DVSV were correlated with R2 = 0.86, 0.80, and 0.86 for PV, T, and NL, respectively. The mean bias ± SE (± LOA) between DLDM‐KA and DVSV was significantly non‐zero with −19.6 ± 5.1% (± 31.0%), −20.8 ± 4.4% (± 29.0%), and −18.1 ± 5.3% (± 31.1%) for PV, T, and NL, respectively. Conclusions: The summation of Aimage in PV was underestimated relative to Aadmin. Only by accounting for respiratory motion, limited spatial resolution, and PET/CT co‐registration errors through VOI expansion was Aimage, on average, equal to Aadmin. The differences between DLDM and DVSV were not clinically relevant, though DLDM‐KA was approximately 20% greater than DVSV. Given the high quantitative accuracy of dose calibrators and challenges associated with accurate 90Y‐PET/CT quantification, LDMKA is the preferred algorithm for accurate 90Y‐PET/CT‐based dosimetry following 90Y‐RE. [ABSTRACT FROM AUTHOR]

Background: Following yttrium‐90 radioembolization (90Y‐RE), 90Y‐PET/CT and 90Y‐SPECT/CT imaging provide the means to calculate the voxelized absorbed dose distribution. Given the widespread use of the two imaging modalities and lack of well‐established standardized dosimetry protocols for 90Y‐RE, there is a clinical need to systematically investigate and evaluate differences in the performance of voxel‐based dosimetry between 90Y‐PET/CT and 90Y‐SPECT/CT. Purpose: To quantitatively analyze and compare 90Y‐PET/CT and 90Y‐SPECT/CT‐based dosimetry following 90Y‐RE. Methods: 90Y‐PET/CT and 90Y‐SPECT/CT imaging was acquired for 35 patients following 90Y‐RE with TheraSphere for the treatment of unresectable hepatocellular carcinoma. Dosimetry was performed using the local deposition method with known activity and the mean dose (Dmean) was calculated for perfused liver volumes (PV), tumors (T), and perfused normal livers (NL). Additionally, the absorbed dose to x% of the volume (Dx, x ∈$ \in $ [5%, 10%, ..., 90%, 95%]) and the volume receiving y Gy (Vy, y ∈$ \in $ [10 Gy, 20 Gy, ..., 190 Gy, 200 Gy]) were calculated for T and NL, respectively. Dose metrics were compared using linear regression, Bland‐Altman analysis, and statistical testing. Results: Both 90Y‐SPECT/CT and 90Y‐PET/CT‐based tumor Dmean were strongly correlated (R2 ≥ 0.90) with Dx, excluding metrics on the extrema. Intra‐modality comparisons of various Dx and Vy metrics yielded statistically significant differences (ANOVA, p < 0.001) for both90Y‐PET/CT and 90Y‐SPECT/CT. Based on statistical testing, only Dx metrics separated by greater than 20%–30% coverage, and only Vy metrics separated by greater than 40–70 Gy, reported significant differences. For PV, there was a strong correlation (R2 ≥ 0.99) between Dmean derived separately from 90Y‐PET/CT and 90Y‐SPECT/CT imaging. The strength of the correlation was slightly reduced for T and NL with R2 = 0.91 and R2 = 0.95, respectively. For PV, the mean bias ± standard error (SE) and 95% limits of agreement (LOA) between Dmean from the two modalities was effectively zero with ‐0.8 ± 0.4% (± 2.5%). For T and NL, the mean bias ± SE (± LOA) was ‐14.5 ± 3.7% (± 24%) and 9.4 ± 4.7% (± 27%), respectively. Conclusion: The strong correlation between Dmean and Dx suggests information from multiple dose metrics (e.g., D70 and Dmean) is largely redundant when establishing dose‐response relationships in 90Y‐RE. Dmean is highly correlated between 90Y‐PET/CT and 90Y‐SPECT/CT‐based dosimetry, for all liver VOIs. Relative to 90Y‐SPECT/CT, 90Y‐PET/CT, on average, yielded higher Dmean to tumors (14%) and lower Dmean to perfused normal livers (9%). Absorbed dose differences for perfused liver volumes between 90Y‐SPECT/CT and 90Y‐PET/CT were negligible. [ABSTRACT FROM AUTHOR]

Background: The calculation of the net administered activity (Aadmin) in patients undergoing 90Y‐radioembolization is essential for dosimetry and radiation safety, yet current methods for measuring residual 90Y activity are often associated with high uncertainty. Therefore, an accurate, robust, and clinically viable method for the determination of Aadmin across approved 90Y microsphere devices is desirable. Purpose: We report on a novel method to determine Aadmin by leveraging the quantitative capabilities of SPECT/CT to measure 90Y‐emission in vivo from patients following 90Y‐radioembolization with glass or resin microspheres. Methods: 90Y‐SPECT/CT attenuation‐corrected count data from 147 sequential 90Y‐radioembolization patients was used for this analysis. Aadmin was calculated as part of routine clinical practice via the exposure rate differences between the initial 90Y‐vial and the 90Y‐residual jar. This served as our gold standard measure of Aadmin. Patient data for each microsphere device were separated into training and testing cohorts to first develop regression models and then to independently assess model performance. The training cohorts were divided into four groups: first, based on the microsphere device (glass or resin), and second, based on the SPECT volume used to calculate counts (the full SPECT field of view (FOV) or liver only (VOIliver)). Univariate linear regression models were generated for each group to predict Aadmin based on 90Y‐SPECT data from the training cohorts. Leave‐one‐out cross validation was implemented to estimate variability in model parameters. To assess performance, linear models derived from the training cohort were applied to 90Y‐SPECT data from the testing cohort. A comparison of the models between microspheres devices was also performed. Results: Linear models derived from the glass and resin training cohorts demonstrated a strong, positive correlation between 90Y‐SPECT image counts and Aadmin for VOIliver and FOV with R2 > 0.98 in all cases. In the glass training cohort, model accuracy (100%—absolute mean prediction error) and precision (95% prediction intervals of mean prediction error) were 99.0% and 15.4% for the VOIliver and 99.7% and 17.5% for the FOV models, respectively. In the resin training cohort, the corresponding values were 98.6% and 16.7% for VOIliver and > 99.9% and 11.4% for the FOV models, respectively. The application of these linear models to 90Y‐SPECT data from the testing cohort showed Aadmin prediction errors to have high accuracy and precision for both microsphere devices. For the glass testing cohort, accuracy (precision) was 96.9% (19.6%) and 98.8% (21.1%) for the VOIliver and FOV models, respectively. The corresponding values for the resin training cohort were 97.3% (26.2%) and 98.5% (25.7%) for the VOIliver and FOV models, respectively. The slope of the linear models between the two microsphere devices was observed to be significantly different with resin microspheres generating 48%–49% more SPECT counts for equivalent 90Y activity based on each device manufacturer's activity calibration process. Conclusion: 90Y‐SPECT image counts can reliably predict (accuracy > 95% and precision < 18%) Aadmin after 90Y‐radioembolization, with performance characteristics essentially equivalent for both glass and resin microspheres. There is a clear indication that activity calibrations are fundamentally different between the two microsphere devices. [ABSTRACT FROM AUTHOR]

Background: Yttrium-90 (90Y) radioembolization is increasingly being utilized with curative intent. While single-compartment doses with respect to the perfused volume for the complete pathologic necrosis (CPN) of tumors have been reported, the actual doses delivered to the tumor and at-risk margins that leads to CPN have hitherto not been estimated. We present an ablative dosimetry model that calculates the dose distribution for tumors and at-risk margins based on numerical mm-scale dose modeling and the available clinical CPN evidence and report on the necessary dose metrics needed to achieve CPN following 90Y-radioembolization. Methods: Three-dimensional (3D) activity distributions (MBq/voxel) simulating spherical tumors were modeled with a 121 × 121 × 121 mm3 soft tissue volume (1 mm3 voxels). Then, 3D dose distributions (Gy/voxel) were estimated by convolving 3D activity distributions with a 90Y 3D dose kernel (Gy/MBq) sized 61 × 61 × 61 mm3 (1 mm3 voxels). Based on the published data on single-compartment segmental doses for the resected liver samples of HCC tumors showing CPN after radiation segmentectomy, the nominal voxel-based mean tumor dose ( D m e a n C P N ), point dose at tumor rim ( D r i m C P N ), and point dose 2 mm beyond the tumor boundary ( D 2 m m C P N ), which are necessary to achieve CPN, were calculated. The single-compartment dose prescriptions to required achieve CPN were then analytically modeled for more general cases of tumors with diameters d t = 2, 3, 4, 5, 6, and 7 cm and with tumor-to-normal-liver uptake ratios T : N = 1:1, 2:1, 3:1, 4:1, and 5:1. Results: The nominal case defined to estimate the doses needed for CPN, based on the previously published clinical data, was a single hyperperfused tumor with a diameter of 2.5 cm and T : N = 3:1, treated with a single-compartment segmental dose of 400 Gy. The voxel-level doses necessary to achieve CPN were 1053 Gy for the mean tumor dose, 860 Gy for the point dose at the tumor boundary, and 561 Gy for the point dose at 2 mm beyond the tumor edge. The single-compartment segmental doses necessary to satisfy the criteria for CPN in terms of the mean tumor dose, point dose at the tumor boundary, and the point dose at 2 mm beyond the tumor edge were tabulated for a range of tumor diameters and tumor-to-normal-liver uptake ratios. Conclusions: The analytical functions that describe the relevant dose metrics for CPN and, more importantly, the single-compartment dose prescriptions for the perfused volume needed to achieve CPN are reported for a large range of conditions in terms of tumor diameters (1–7 cm) and T : N uptake ratios (2:1–5:1). [ABSTRACT FROM AUTHOR]

Purpose: To investigate the accuracy and biases of predicted lung shunt fraction (LSF) and lung dose (LD) calculations via 99mTc‐macro‐aggregated albumin (99mTc‐MAA) planar imaging for treatment planning of 90Y‐microsphere radioembolization. Methods and materials: LSFs in 52 planning and LDs in 44 treatment procedures were retrospectively calculated, in consecutive radioembolization patients over a 2 year interval, using 99mTc‐MAA planar and SPECT/CT imaging. For each procedure, multiple planar LSFs and LDs were calculated using different: (1) contours, (2) views, (3) liver 99mTc‐MAA shine‐through compensations, and (4) lung mass estimations. The accuracy of each planar‐based LSF and LD methodology was determined by calculating the median (range) absolute difference from SPECT/CT‐based LSF and LD values, which have been demonstrated in phantom and patient studies to more accurately and reliably quantify the true LSF and LD values. Results: Standard‐of‐care LSF using geometric mean of lung and liver contours had median (range) absolute over‐estimation of 4.4 percentage points (pp) (0.9 to 11.9 pp) from SPECT/CT LSF. Using anterior views only decreased LSF errors (2.4 pp median, −1.1 to +5.7 pp range). Planar LD over‐estimations decreased when using single‐view versus geometric‐mean LSF (1.3 vs. 2.6 Gy median and 7.2 vs. 18.5 Gy maximum using 1000 g lung mass) but increased when using patient‐specific versus standard‐man lung mass (2.4 vs. 1.3 Gy median and 11.8 vs. 7.2 Gy maximum using single‐view LSF). Conclusions: Calculating planar LSF from lung and liver contours of a single view and planar LD using that same LSF and 1000 g lung mass was found to improve accuracy and minimize bias in planar lung dosimetry. [ABSTRACT FROM AUTHOR]

Purpose: There are no published data on organ doses following intra‐hepatic‐arterial administration of 99mTc‐macroaggregated‐albumin (IHA 99mTc‐MAA) routinely used in 90Y‐radioembolization treatment planning to assess intra‐ and extra‐hepatic depositions and calculate lung‐shunt‐fraction (LSF). We propose a method to model the organ doses following IHA 99mTc‐MAA that incorporates three in vivo constituent biodistributions, the 99mTc‐MAA that escape the liver due to LSF, and the 99mTc‐MAA dissociation fraction (DF). Methods: The potential in vivo biodistributions for IHA 99mTc‐MAA are: Liver‐Only MAA with all activity sequestered in the liver (LSF = 0&DF = 0), Intravenous MAA with all activity transferred intravenously as 99mTc‐MAA (LSF = 1&DF = 0), and Intravenous Pertechnetate with all activity is transferred intravenously as 99mTc‐pertechnetate (LSF = 0&DF = 1). Organ doses for Liver‐Only MAA were determined using OLINDA/EXM 2.2, where liver was modeled as the source organ containing 99mTc‐MAA, while those for Intravenous MAA and Intravenous Pertechnetate were from ICRP 128. Organ doses for the general case can be determined as a weighted‐linear‐combination of the three constituent biodistributions depending on the LSF and DF. The maximum‐dose scenario was modeled by selecting the highest dose rate for each organ amongst the three constituent cases. Results: For Liver‐Only MAA, the liver as source organ received the highest dose at 98.6 and 126 mGy/GBq for the adult male and adult female phantoms, respectively; all remaining organs received <27 and <32 mGy/GBq. For Intravenous MAA, the lung as source organ received the highest dose at 66 and 97 mGy/GBq; all remaining organs received <16 and <21 mGy/GBq. The organ with the highest dose for Intravenous Pertechnetate was the upper‐large‐intestinal wall at 56 and 73 mGy/GBq; all remaining organs received <26 and <34 mGy/GBq. The liver and lung doses for the maximum‐dose scenario with 5 mCi (185 MBq) 99mTc‐MAA were estimated at 18.2 and 12.2 mGy, and 23.3 and 17.9 mGy, for the adult male and adult female phantoms, respectively. Conclusion: Organ dose estimates following IHA 99mTc‐MAA based on constituent biodistribution models and patient‐specific LSF and DF values have been derived. Liver and lung were the organs with highest dose, receiving at most 15–25 mGy in the maximum‐dose scenario, following 5 mCi IHA 99mTc‐MAA. [ABSTRACT FROM AUTHOR]

Purpose: Current treatment planning for 90Y radioembolization estimates lung mean dose (LMD) by measuring the lung shunt fraction (LSF) from 99mTc‐macroaggregated albumin (MAA) planar imaging and assuming a 1‐kg lung mass. This methodology, however, overestimates LSF and LMD and could therefore unnecessarily limit the dose to target volume(s). We propose an improved LMD calculation that derives LSF from 99mTc‐MAA SPECT/CT and the patient‐specific lung mass from diagnostic chest CT. Furthermore, we investigated the errors in lung mass, LSF, and LMD arising from contour variability in patient data in order to estimate the precision of our proposed methodology. Methods: Our proposed LMD (LMDnew) calculation consisted of the following steps: (a) estimate liver counts from the MAA SPECT/CT liver contour; (b) estimate total lung counts by multiplying density (counts/g) from the MAA SPECT/CT left‐lung contour by the total lung mass (g) from the diagnostic CT lung contours; (c) compute LSFnew from liver and lung counts; (d) calculate LMDnew using LSFnew and the total lung mass from the diagnostic CT (Mnew). LMDnew, LSFnew, and Mnew estimates were compared to standard model values (LMDclin, LSFclin, and 1 kg, respectively) in 52 consecutive patients with hepatocellular carcinoma who underwent radioembolization using 90Y glass microspheres. The precision of our methodology was quantified by varying lung and liver contours in the same patient population and calculating the resulting relative errors in the liver count, lung count, and lung mass measurements. Results: The median Mnew was 839 g (range, 550–1178 g) for men and 731 g (range, 548–869 g) for women. The median LSFnew was 0.02 (range, 0.01–0.11), while the median LMDnew was 4.9 Gy (range, 0.3–25.5 Gy). Mnew, LSFnew, and LMDnew were significantly lower than Mclin, LSFclin, and LMDclin, with respective relative mean (±SD) differences of −20% (±16%) for Mnew, −63% (±15%) for LSFnew, and −53% (±23%) for LMDnew. The estimated 1‐sigma uncertainties in Mnew, LSFnew, and LMDnew were 9%, 10%, and 13%, respectively. Conclusions: We derived a method to calculate lung mass and LSF using routinely available diagnostic chest CT and 99mTc‐MAA SPECT/CT. More importantly, we systematically quantified the errors in our measurements to establish the precision of the estimated lung dose (13%). The proposed methodology provides a more accurate LMD and an estimate of its precision, which will improve treatment and retreatment planning for 90Y radioembolizations. [ABSTRACT FROM AUTHOR]