Estimation of kidney doses from [177Lu]Lu-DOTA-TATE PRRT using single time point post-treatment SPECT/CT.

BACKGROUND: Dosimetry after [177Lu]Lu-DOTA-TATE therapy can be demanding for both patients and the clinical service due to the need for imaging at several time points. In this work we compare three methods of single time point (STP) kidney dosimetry after [177Lu]Lu-DOTA-TATE therapy with a multiple time point (MTP) dosimetry method. METHOD: Method 1 (MTP): Kidney doses were calculated from 31 patients including 107 therapy cycles. Post-therapy SPECT images were acquired on day 0, 4 and 7 along with a CT scan on day 4. A mono-exponential fit was used to calculate kidney doses using cycle specific data. Method 2 (Consistent effective half-life): The effective half-life [Formula: see text] calculated in cycle 1 was assumed consistent for subsequent cycles of therapy and the activity scaled using a single day 3-5 SPECT/CT. Methods 3 and 4 (Hänscheid and Madsen approximations): The Hänscheid approximation and Madsen approximation were both evaluated using a single SPECT/CT acquired on day 0, 4 and 7. All STP methods were compared to the MTP method for accuracy. RESULTS: Using the MTP method, mean right and left kidney doses were calculated to be 2.9 ± 1.1 Gy and 2.8 ± 0.9 Gy respectively and the population [Formula: see text] was 56 ± 13 h. For the consistent [Formula: see text], Hänscheid and Madsen methods, the percentage of results within ± 20% of MTP method were 96% (n = 70), 95% (n = 80) and 94% (n = 80) respectively. CONCLUSION: All three single time point methods had > 94% of results within ± 20% of the MTP method, however the consistent [Formula: see text] method resulted in the highest alignment with the MTP method and is the only method which allows for calculation of the patient-specific [Formula: see text]. If only a single scan can be performed, day 4 is optimal for kidney dosimetry where the Hänscheid or Madsen approximation can be implemented with good accuracy.

Impact of the Reference Multiple-Time-Point Dosimetry Protocol on the Validity of Single-Time-Point Dosimetry for [177Lu]Lu-PSMA-I&T Therapy.

Internal dosimetry supports safe and effective patient management during radionuclide therapy. Yet, it is associated with high clinical workload, costs, and patient burden, as patient scans at multiple time points (MTPs) must be acquired. Dosimetry based on imaging at a single time point (STP) has continuously gained popularity. However, MTP protocols, used as a reference to judge the validity of STP dosimetry, differ depending on local requirements and deviate from the unknown patient-specific ground truth pharmacokinetics. The aim of this study was to compare the error and optimum time point for different STP approaches using different reference MTP protocols. Methods: Whole-body SPECT/CT scans of 7 patients (7.4-8.9 GBq of [177Lu]Lu-PSMA-I&T) were scheduled at 24, 48, 72, and 168 h after injection. Sixty lesions, 14 kidneys, and 10 submandibular glands were delineated in the SPECT/CT data. Two curve models, that is, a mono- and a biexponential model, were fitted to the MTP data, in accordance with goodness-of-fit analysis (coefficients of variation, sum of squared errors). Three population-based STP approaches were compared: one method published by Hänscheid et al., one by Jackson et al., and one using population-based effective half-lives in the mono- or biexponential curve models. Percentage differences between STP and MTP dosimetry were evaluated. Results: Goodness-of-fit parameters show that a monoexponential function and a biexponential function with shared population-based parameters and physical tail are reasonable reference models. When comparing both reference models, we observed maximum differences of -44%, -19%, and -28% in the estimated absorbed doses for lesions, kidneys, and salivary glands, respectively. STP dosimetry with an average deviation of less than 10% from MTP dosimetry may be feasible; however, this deviation and the optimum imaging time point showed a dependence on the chosen reference protocol. Conclusion: STP dosimetry for [177Lu]Lu-PSMA therapy is promising to boost the integration of dosimetry into clinical routine. According to our patient cohort, 48 h after injection may be regarded as a compromise for STP dosimetry for lesions and at-risk organs. The results from this analysis show that a common gold standard for dosimetry is desirable to allow for reliable and comparable STP dosimetry.

A review of 177Lu dosimetry workflows: how to reduce the imaging workloads?

177 Lu radiopharmaceutical therapy is a standardized systemic treatment, with a typical dose of 7.4 GBq per injection, but its response varies from patient to patient. Dosimetry provides the opportunity to personalize treatment, but it requires multiple post-injection images to monitor the radiopharmaceutical's biodistribution over time. This imposes an additional imaging burden on centers with limited resources. This review explores methods to lessen this burden by optimizing acquisition types and minimizing the number and duration of imaging sessions. After summarizing the different steps of dosimetry and providing examples of dosimetric workflows for 177 Lu -DOTATATE and 177 Lu -PSMA, we examine dosimetric workflows based on a reduced number of acquisitions, or even just one. We provide a non-exhaustive description of simplified methods and their assumptions, as well as their limitations. Next, we detail the specificities of each normal tissue and tumors, before reviewing dose-response relationships in the literature. In conclusion, we will discuss the current limitations of dosimetric workflows and propose avenues for improvement.

Organ and tumor dosimetry including method simplification for [177Lu]Lu-PSMA-I&T for treatment of metastatic castration resistant prostate cancer.

BACKGROUND: Internal dosimetry in individual patients is essential for safe and effective radioligand therapy. Multiple time point imaging for accurate dosimetry is time consuming and hence can be demanding for nuclear medicine departments as well as patients. The objectives of this study were (1) to assess absorbed doses to organs at risk and tumor lesions for [177Lu]Lu-PSMA-I&T using whole body SPECT imaging and (2) to investigate possible simplified dosimetry protocols. METHODS: This study included 16 patients each treated with 4 cycles of [177Lu]Lu-PSMA-I&T. They underwent quantitative whole body SPECT/CT imaging (3 bed positions) at four time points (TP) comprising 2 h, 24 h, 48 h and 72-168 h post-injection (p.i.). Full 3D dosimetry (reference method) was performed for all patients and dose cycles for organs at risk (kidneys, parotid glands and submandibular glands) and up to ten tumor lesions per patient (resulting in 90 lesions overall). The simplified dosimetry methods (SM) included (1) generating time activity curves for subsequent cycles using a single TP of imaging applying the kinetics of dose cycle 1, and for organs at risk also (2) simple extrapolation from dose cycle 1 and (3) from both, dose cycle 1 and 2. RESULTS: Normalized absorbed doses were 0.71 ± 0.32 mGy/MBq, 0.28 ± 0.12 mGy/MBq and 0.22 ± 0.08 mGy/MBq for kidneys, parotid glands and submandibular glands, respectively. Tumor doses decreased from 3.86 ± 3.38 mGy/MBq in dose cycle 1 to 2.01 ± 2.65 mGy/MBq in dose cycle 4. Compared to the full dosimetry approach the SM 1 using single TP imaging at 48 h p.i. resulted in the most accurate and precise results for the organs at risk in terms of absorbed doses per cycle and total cumulated dose. For tumor lesions better results were achieved using the fourth TP (≥ 72 h p.i.). CONCLUSION: Simplification of safety dosimetry protocols is possible for [177Lu]Lu-PSMA-I&T therapy. If tumor dosimetry is of interest a later imaging TP (≥ 72 h p.i.) should be used/added to account for the slower kinetics of tumors compared to organs at risk.

Toward Single-Time-Point Image-Based Dosimetry of 177Lu-PSMA-617 Therapy.

Radiopharmaceutical therapies (RPTs) with 177Lu-prostate-specific membrane antigen (PSMA) ligands have demonstrated promising results for the treatment of metastatic castration-resistant prostate cancer. The lack of absorbed-dose-effect relationships currently prevents patient-specific activity personalization. To ease the implementation of dosimetry in the routine clinical workflow for RPT, simplified methods such as single-time-point (STP) instead of multiple-time-point (MTP) imaging protocols are required. This work aimed at assessing differences in the time-integrated activity (TIA) of STP versus MTP image-based dosimetry for 177Lu-PSMA-617 therapy. Methods: Twenty metastatic castration-resistant prostate cancer patients with MTP quantitative 177Lu-SPECT imaging data (∼24, 48, and 72 h post injection (p.i.)) available on first and second 177Lu-PSMA-617 therapy cycles were included in this study. Time-activity curves were fitted for kidneys and lesions to derive effective half-lives and yield a reference TIA. STP approaches involved the formula by Hänscheid (STPH) and a prior-information method (STPprior) that uses the effective half-lives from the first therapy cycle. All time points were considered for the STP approaches. Percentage differences (PDs) in TIA between STP and MTP were compared for the second therapy cycle. Results: Using STPH at 48 h p.i. for kidneys showed a -1.3% ± 5.6% PD from MTP, whereas STPprior showed a PD of 4.6% ± 6.2%. The smallest average PDs for the 56 investigated individual lesions were found using STPprior at 48 h p.i., at only 0.4% ± 14.9%, whereas STPH at 72 h p.i. had a smallest PD of -1.9% ± 14.8%. Conclusion: STP dosimetry for 177Lu-PSMA-617 therapy using a single SPECT/CT scan at 48 or 72 h p.i. is feasible, with a PD of less than ±20% compared with MTP. The validity of both STPH and STPprior has been demonstrated. We believe this finding can increase the adoption of dosimetry and facilitate implementation in routine clinical RPT workflows. Doing so will ultimately enable the finding of dose-effect relationships based on fixed therapy activities that may, in future, allow for absorbed-dose-based RPT activity personalization.

Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model.

INTRODUCTION: Estimation of accurate time-integrated activity coefficients (TIACs) and radiation absorbed doses (ADs) is desirable for treatment planning in peptide-receptor radionuclide therapy (PRRT). This study aimed to investigate the accuracy of a simplified dosimetry using a physiologically-based pharmacokinetic (PBPK) model, a nonlinear mixed effect (NLME) model, and single-time-point imaging to calculate the TIACs and ADs of 90Y-DOTATATE in various organs of dosimetric interest and tumors. MATERIALS & METHODS: Biokinetic data of 111In-DOTATATE in tumors, kidneys, liver, spleen, and whole body were obtained from eight patients using planar scintigraphic imaging at T1 = (2.9 ±â€¯0.6), T2 = (4.6 ±â€¯0.4), T3 = (22.8 ±â€¯1.6), T4 = (46.7 ±â€¯1.7) and T5 = (70.9 ±â€¯1.0) h post injection. Serum activity concentration was measured at 5 and 15 min; 0.5, 1, 2, and 4 h; and 1, 2, and 3 d p.i.. A published PBPK model for PRRT, NLME, and a single-time-point imaging datum at different time points were used to calculate TIACs in tumors, kidneys, liver, spleen, whole body, and serum. Relative deviations (RDs) (median [min, max]) between the calculated TIACs from single-time-point imaging were compared to the TIACs calculated from the all-time-points fit. The root mean square error (RMSE) of the difference between the computed ADs from the single-time-point imaging and reference ADs from the all-time point fittings were analyzed. A joint root mean square error RMSEjoint of the ADs was calculated with the RSME from both the tumor and kidneys to sort the time points concerning accurate results for the kidneys and tumor dosimetry. The calculations of TIACs and ADs from the single-time-point dosimetry were repeated using the sum of exponentials (SOE) approach introduced in the literature. The RDs and the RSME of the PBPK approach in our study were compared to the SOE approach. RESULTS: Using the PBPK and NLME models and the biokinetic measurements resulted in a good fit based on visual inspection of the fitted curves and the coefficient of variation CV of the fitted parameters (<50%). T4 was identified being the time point with a relatively low median and range of TIACs RDs, i.e., 5 [1, 21]% and 2 [-15, 21]% for kidneys and tumors, respectively. T4 was found to be the time point with the lowest joint root mean square error RMSEjoint of the ADs. Based on the RD and RMSE, our results show a similar performance as the SOE and NLME model approach. SUMMARY: In this study, we introduced a simplified calculation of TIACs/ADs using a PBPK model, an NLME model, and a single-time-point measurement. Our results suggest a single measurement might be used to calculate TIACs/ADs in the kidneys and tumors during PRRT.

Lu-177-PSMA dosimetry for kidneys and tumors based on SPECT images at two imaging time points.

Background: Personalized dosimetry for Lu-177-PSMA treatment requires multiple-time-point SPECT/CT scans to calculate time-integrated activity (TIA). This study evaluates two-time-point (TTP) methods for TIA calculation for kidneys and tumors. Methods: A total of 18 patients treated with 3.7-7.4 GBq Lu-177 PSMA-617 were analyzed retrospectively, including 18 sets of left and right kidneys, as well as 45 tumors. Four quantitative SPECT/CT (4TP) were acquired at 2 h, 20 h, 40 h, 60 h (n = 11), or 200 h (n = 7) after treatment, and they were fit bi-exponentially as reference. The TTP method was fitted by a mono-exponential washout function using two selected imaging time points for kidneys. For tumors, one uptake and one washout phase were modeled, assuming linear (type I) and same (type II) uptake phase between 0 h to the first time point and mono-exponential washout thereafter. Two single-time-point (STP) methods were also implemented for comparison. TIA calculated by TTP and STP methods were compared with reference to the 4TP TIA. Results: For the kidneys, the TTP methods using 20 h-60 h and 40 h-200 h had smaller mean absolute errors of 8.05 ± 6.05% and 4.95 ± 3.98%, respectively, as compared to other combinations of time points and STP methods. For tumors, the type I and type II TTP methods using 20h-60 h and 40-200 h had smaller mean absolute errors of 6.14 ± 5.19% and 12.22 ± 4.44%, and 8.31 ± 7.16% and 4.48 ± 7.10%, respectively, as compared to other TTP and STP methods. Conclusion: The TTP methods based on later imaging time demonstrated fewer errors than the STP methods in kidney and tumor TIA. Imaging at 20 h-60 h and 40 h-200 h could simplify the dosimetry procedures with fewer TIA estimation errors.

Single-Time-Point Imaging for Dosimetry After [177Lu]Lu-DOTATATE: Accuracy of Existing Methods and Novel Data-Driven Models for Reducing Sensitivity to Time-Point Selection.

Estimation of the time-integrated activity (TIA) for dosimetry from imaging at a single time point (STP) facilitates the clinical translation of dosimetry-guided radiopharmaceutical therapy. However, the accuracy of the STP methods for TIA estimation varies on the basis of time-point selection. We constructed patient data-driven regression models to reduce the sensitivity to time-point selection and to compare these new models with commonly used STP methods. Methods: SPECT/CT performed at time period (TP) 1 (3-5 h), TP2 (days 1-2), TP3 (days 3-5), and TP4 (days 6-8) after cycle 1 of [177Lu]Lu-DOTATATE therapy involved 27 patients with 100 segmented tumors and 54 kidneys. Influenced by the previous physics-based STP models of Madsen et al. and Hänscheid et al., we constructed an STP prediction expression, TIA = A(t) × g(t), in a SPECT data-driven way (model 1), in which A(t) is the observed activity at imaging time t, and the curve, g(t), is estimated with a nonparametric generalized additive model by minimizing the normalized mean square error relative to the TIA derived from 4-time-point SPECT (reference TIA). Furthermore, we fit a generalized additive model that incorporates baseline biomarkers as auxiliary data in addition to the single activity measurement (model 2). Leave-one-out cross validation was performed to evaluate STP models using mean absolute error (MAE) and mean square error between the predicted and reference TIA. Results: At days 3-5, all evaluated STP methods performed very well, with an MAE of less than 7% (between-patient SD of <10%) for both kidneys and tumors. At other TPs, the Madsen method and data-driven models 1 and 2 performed reasonably well (MAEs < 17% for kidneys and < 32% for tumors), whereas the error with the Hänscheid method was substantially higher. The proof of concept of adding baseline biomarkers to the prediction model was demonstrated and showed a moderate enhancement at TP1, especially for estimating kidney TIA (MAE ± SD from 15.6% ± 1.3% to 11.8% ± 1.0%). Evaluations on 500 virtual patients using clinically relevant time-activity simulations showed a similar performance. Conclusion: The performance of the Madsen method and proposed data-driven models is less sensitive to TP selection than is the Hänscheid method. At the earliest TP, which is the most practical, the model incorporating baseline biomarkers outperforms other methods that rely only on the single activity measurement.

Accuracy and uncertainty analysis of reduced time point imaging effect on time-integrated activity for 177Lu-DOTATATE PRRT in patients and clinically realistic simulations.

BACKGROUND: Dosimetry promises many advantages for radiopharmaceutical therapies but repeat post-therapy imaging for dosimetry can burden both patients and clinics. Recent applications of reduced time point imaging for time-integrated activity (TIA) determination for internal dosimetry following 177Lu-DOTATATE peptide receptor radionuclide therapy have shown promising results that allow for the simplification of patient-specific dosimetry. However, factors such as scheduling can lead to sub-optimal imaging time points, but the resulting impact on dosimetry accuracy is still under investigation. We use four-time point 177Lu SPECT/CT data for a cohort of patients treated at our clinic to perform a comprehensive analysis of the error and variability in time-integrated activity when reduced time point methods with various combinations of sampling points are employed. METHODS: The study includes 28 patients with gastroenteropancreatic neuroendocrine tumors who underwent post-therapy SPECT/CT imaging at approximately 4, 24, 96, and 168 h post-therapy (p.t.) following the first cycle of 177Lu-DOTATATE. The healthy liver, left/right kidney, spleen and up to 5 index tumors were delineated for each patient. Time-activity curves were fit with either monoexponential or biexponential functions for each structure, based on the Akaike information criterion. This fitting was performed using all 4 time points as a reference and various combinations of 2 and 3 time points to determine optimal imaging schedules and associated errors. 2 commonly used methods of single time point (STP) TIA estimation are also evaluated. A simulation study was also performed with data generated by sampling curve fit parameters from log-normal distributions derived from the clinical data and adding realistic measurement noise to sampled activities. For both clinical and simulation studies, error and variability in TIA estimates were estimated with various sampling schedules. RESULTS: The optimal post-therapy imaging time period for STP estimates of TIA was found to be 3-5 days (71-126 h) p.t. for tumor and organs, with one exception of 6-8 days (144-194 h) p.t. for spleen with one STP approach. At the optimal time point, STP estimates give mean percent errors (MPE) within ± 5% and SD < 9% across all structures with largest magnitude error for kidney TIA (MPE = - 4.1%) and highest variability also for kidney TIA (SD = 8.4%). The optimal sampling schedule for 2TP estimates of TIA is 1-2 days (21-52 h) p.t. followed by 3-5 days (71-126 h) p.t. for kidney, tumor, and spleen. Using the optimal sampling schedule, the largest magnitude MPE for 2TP estimates is 1.2% for spleen and highest variability is in tumor with SD = 5.8%. The optimal sampling schedule for 3TP estimates of TIA is 1-2 days (21-52 h) p.t. followed by 3-5 days (71-126 h) p.t. and 6-8 days (144-194 h) p.t. for all structures. Using the optimal sampling schedule, the largest magnitude MPE for 3TP estimates is 2.5% for spleen and highest variability is in tumor with SD = 2.1%. Simulated patient results corroborate these findings with similar optimal sampling schedules and errors. Many sub-optimal reduced time point sampling schedules also exhibit low error and variability. CONCLUSIONS: We show that reduced time point methods can be used to achieve acceptable average TIA errors over a wide range of imaging time points and sampling schedules while maintaining low uncertainty. This information can improve the feasibility of dosimetry for 177Lu-DOTATATE and elucidate the uncertainty associated with non-ideal conditions.

Impact of Single-Time-Point Estimates of 177Lu-PRRT Absorbed Doses on Patient Management: Validation of a Trained Multiple-Linear-Regression Model in 159 Patients and 477 Therapy Cycles.

Dosimetry after 177Lu-DOTATATE peptide receptor radionuclide therapy (PRRT) enables estimation of radiation doses absorbed by normal organs and target lesions. This process is time-consuming and requires multiple posttreatment studies on several subsequent days. In a previous study, we described a newly developed multiple-linear-regression model to predict absorbed doses (ADs) from a single-time-point (STP) posttreatment study acquired 168 h after the first infusion and 24 h after the following ones, with similar results to the standard multiple-time-point (MTP) protocol. The present study aimed to validate this model in a large patient cohort and to assess whether STP dosimetry affects patient management decisions compared with our MTP protocol. Methods: Quantitative 177Lu-DOTATATE SPECT/CT post-PRRT data from 159 consecutive patients (172 therapies, 477 therapy cycles) were retrospectively analyzed. ADs obtained from an STP model were compared with those obtained using an MTP model. We evaluated the impact of the STP model on the decision on whether PRRT should be stopped because of an expected kidney AD exceeding the safety threshold. We hypothesized that patient management based on the STP model does not differ from that based on the MTP model in at least 90% of the cases. Results: There was no difference in management decisions between the MTP and STP models in 170 of 172 therapies (98.8%). A Fisher χ2 test for combined probabilities produced a composite P value of 0.0003. Mean cumulative AD relative differences between the STP and MTP models were 0.8% ± 8.0%, -7.7% ± 4.8%, 0.0% ± 11.4%, -2.8% ± 6.3%, and -2.1% ± 18.4% for kidneys, bone marrow, liver, spleen, and tumors, respectively (Pearson r = 0.99 for all), for patients who underwent 4 therapy cycles. Similar results were obtained with fewer therapy cycles. Conclusion: Estimated radiation ADs and patient management decisions were similar with the STP and MTP models. The STP model can simplify the dosimetry process while also reducing scanner and staff time and improving patient comfort.

Theoretical aspects on the use of single-time-point dosimetry for radionuclide therapy.

Objective. This study considers the error distributions for time-integrated activity (TIA) of single-time-point (STP) methods for patient-specific dosimetry in radionuclide therapy.Approach. The general case with the same pharmaceutical labelled with different radionuclides for imaging and therapy are considered for a mono-exponential time-activity curve. Two methods for STP dosimetry, both based on the combination of one activity estimate with the population-mean effective decay constant, are investigated. The cumulative distribution functions (CDFs) and the probability density functions for the two methods are analytically derived for arbitrary distributions of the biological decay constant. The CDFs are used for determining 95% coverage intervals of the relative errors for different combinations of imaging time points, physical decay constants, and relative standard deviations of the biological decay constant. Two examples, in the form of kidney dosimetry in [177Lu]Lu-DOTA-TATE therapy and tumour dosimetry for Na[131I]I therapy for thyroid cancer with dosimetry based on imaging of Na[124I]I, are also studied in more detail with analysis of the sensitivity with respect to errors in the mean biological decay constant and to higher moments of the distribution.Main results. The distributions of the relative errors are negatively skewed, potentially leading to the situation that some TIA estimates are highly underestimated even if the majority of estimates are close to the true value.Significance. The main limitation of the studied STP dosimetry methods is the risk of large underestimations of the TIA.

Is a single late SPECT/CT based kidney 177Lu-dosimetry superior to hybrid dosimetry with sequential multiple time-point whole-body planar scans in combination with an early SPECT/CT?

PURPOSE: The aim is to assess the impact of different imaging-protocols on image-based kidney dosimetry in 177Lu labelled peptide receptor radiotherapies. METHODS: Kidney data of five [177Lu]Lu-OPS201 injected pigs and a 3D printed phantom were used for comparing the absorbed doses and time-integrated activity coefficients calculated based on the following imaging-protocols: A-) multiple time-point SPECT/CTs, B-) multiple time-point planar scans in combination with one SPECT/CT, C-) single time-point SPECT/CT. In addition, the influence of late scan time-points on kidney dosimetry was investigated by sequentially eliminating scan data at > 100 h from the pig/phantom datasets for imaging-protocols A and B. RESULTS: Compared to imaging-protocol A, absorbed doses based on imaging-protocols B and C (scans at > 24 h post-injection) were always lower (differences > 34%). The best agreement in absorbed dose was achieved by imaging-protocol C at âˆ¼ 100 h post-injection (difference: 4%). Regarding the phantom/pig experiments, eliminating scan data at > 100 h post-injection increased the time-integrated activity coefficients calculated based on imaging-protocols A and B by up to 83%. CONCLUSION: While imaging-protocol A is accurate if scans at >∼100 h are included, it is time-consuming. In addition to being time-consuming, imaging-protocol B shows high differences associated with organ-count overlay, a lack of accuracy concerning the geometric mean based 2D attenuation correction, and 2D background subtraction due to the inhomogeneous and time-varying background contributions. Our findings indicate that dosimetry based on imaging-protocol C, if appropriately performed, provides similar kidney absorbed doses compared to imaging-protocol A, while only a single scan time-point is necessary.

Feasibility of Single-Time-Point Dosimetry for Radiopharmaceutical Therapies.

Because of challenges in performing routine personalized dosimetry in radiopharmaceutical therapies, interest in single-time-point (STP) dosimetry, particularly using only a single SPECT scan, is on the rise. Meanwhile, there are questions about the reliability of STP dosimetry, with limited independent validations. In the present work, we analyzed 2 STP dosimetry methods and evaluated dose errors for several radiopharmaceuticals based on effective half-life distributions. Methods: We first challenged the common assumption that radiopharmaceutical effective half-lives across the population are gaussian-distributed (i.e., follow a normal distribution). Then, dose accuracy was estimated using 2 STP dosimetry methods for a wide range of potential post injection (p.i.) scan time points for different radiopharmaceuticals applied to neuroendocrine tumors and prostate cancer. The accuracy and limitations of each of the STP methods were discussed. Results: A lognormal distribution was more appropriate for capturing effective half-life distributions. The STP framework was promising for dosimetry of 177Lu-DOTATATE and for kidney dosimetry of different radiopharmaceuticals (errors < 30%). Meanwhile, for some radiopharmaceuticals, STP accuracy was compromised (e.g., in bone marrow and tumors for 177-labeled prostate-specific membrane antigen [PSMA])). The optimal SPECT scanning time for 177Lu-DOTATATE was approximately 72 h p.i., whereas 48 h p.i. was better for 177Lu-PSMA. Conclusion: Simplified STP dosimetry methods may compromise the accuracy of dose estimates, with some exceptions, such as for 177Lu-DOTATATE and for kidney dosimetry in different radiopharmaceuticals. Simplified personalized dosimetry in the clinic continues to be challenging. On the basis of our results, we make suggestions and recommendations for improved personalized dosimetry using simplified imaging schemes.

Streamlined Schemes for Dosimetry of 177Lu-Labeled PSMA Targeting Radioligands in Therapy of Prostate Cancer.

(Background) Aim of this retrospective analysis was to investigate in mCRPC patients treated with [177Lu]Lu-PSMA-617 whether the absorbed dose (AD) in organs at risk (OAR, i.e., kidneys and parotid glands) can be calculated using simplified methodologies with sufficient accuracy. For this calculation, results and kinetics of the first therapy cycle were used. (Methods) 46 patients treated with 2 to 6 cycles of [177Lu]Lu-PSMA-617 were included. As reference (current clinical standard) full dosimetry of the OAR based on quantitative imaging (whole body scintigraphy and quantitative SPECT/CT at 2, 24, 48 and 72 h p.i.) for every cycle was used. Alternatively, two dosimetry schemes, simplified in terms of image acquisition and dose calculation, were established, both assuming nearly unchanged kinetics of the radiopharmaceutical for subsequent cycles. (Results) In general, for both OAR the simplified methods provided results that were consistent with the dosimetric reference method, both per cycle and in terms of cumulative AD. Best results were obtained when imaging was performed at 48 h p.i. in each of the subsequent cycles. However, both simplified methods tended to underestimate the cumulative AD. (Conclusion) Simplified dosimetry schemes are feasible to tailor multi-cycle [177Lu]Lu-PSMA-targeted therapies.

Influence of sampling schedules on [177Lu]Lu-PSMA dosimetry.

BACKGROUND: Individualized dosimetry is recommended for [177Lu]Lu-PSMA radioligand therapy (RLT) which is resource-intensive and protocols are often not optimized. Therefore, a simulation study was performed focusing on the determination of efficient optimal sampling schedules (OSS) for renal and tumour dosimetry by investigating different numbers of time points (TPs). METHODS: Sampling schedules with 1-4 TPs were investigated. Time-activity curves of the kidneys and two tumour lesions were generated based on a physiologically based pharmacokinetic (PBPK) model and biokinetic data of 13 patients who have undergone [177Lu]Lu-PSMA I&T therapy. Systematic and stochastic noise of different ratios was considered when modelling time-activity data sets. Time-integrated activity coefficients (TIACs) were estimated by simulating the hybrid planar/SPECT method for schedules comprising at least two TPs. TIACs based on one single SPECT/CT measurement were estimated using an approximation for reducing the number of fitted parameters. For each sampling schedule, the root-mean-squared error (RMSE) of the deviations of the simulated TIACs from the ground truths for 1000 replications was used as a measure for accuracy and precision. RESULTS: All determined OSS included a late measurement at 192 h p.i., which was necessary for accurate and precise tumour TIACs. OSS with three TPs were identified to be 3-4, 96-100 and 192 h with an additional SPECT/CT measurement at the penultimate TP. Kidney and tumour RMSE of 6.4 to 7.7% and 6.3 to 7.8% were obtained, respectively. Shortening the total time for dosimetry to e.g. 96 h resulted in kidney and tumour RMSE of 6.8 to 8.3% and 9.1 to 11%, respectively. OSS with four TPs showed similar results as with three TPs. Planar images at 4 and 68 h and a SPECT/CT shortly after the 68 h measurement led to kidney and tumour RMSE of 8.4 to 12% and 12 to 16%, respectively. One single SPECT/CT measurement at 52 h yielded good approximations for the kidney TIACs (RMSE of 7.0%), but led to biased tumour TIACs. CONCLUSION: OSS allow improvements in accuracy and precision of renal and tumour dosimetry for [177Lu]Lu-PSMA therapy with potentially less effort. A late TP is important regarding accurate tumour TIACs.

Improving Gastric Cancer Outcome Prediction Using Single Time-Point Artificial Neural Network Models.

In cancer studies, the prediction of cancer outcome based on a set of prognostic variables has been a long-standing topic of interest. Current statistical methods for survival analysis offer the possibility of modelling cancer survivability but require unrealistic assumptions about the survival time distribution or proportionality of hazard. Therefore, attention must be paid in developing nonlinear models with less restrictive assumptions. Artificial neural network (ANN) models are primarily useful in prediction when nonlinear approaches are required to sift through the plethora of available information. The applications of ANN models for prognostic and diagnostic classification in medicine have attracted a lot of interest. The applications of ANN models in modelling the survival of patients with gastric cancer have been discussed in some studies without completely considering the censored data. This study proposes an ANN model for predicting gastric cancer survivability, considering the censored data. Five separate single time-point ANN models were developed to predict the outcome of patients after 1, 2, 3, 4, and 5 years. The performance of ANN model in predicting the probabilities of death is consistently high for all time points according to the accuracy and the area under the receiver operating characteristic curve.

Predicting the Outcomes of Subjects With Severe Community-Acquired Pneumonia Using Monocyte Human Leukocyte Antigen-DR.

BACKGROUND: The objective was to study the level of monocyte-human leukocyte antigen-DR (mHLA-DR), an immune function-related biomarker, at 24 h after admission, to predict the outcomes of subjects with severe pneumonia. METHODS: Subjects with severe community-acquired pneumonia (n = 102) were included in the study. Blood samples were collected from each subject 24 h after admission. Data regarding age, sex, PaO2 /FIO2, comorbidities, occurrence of altered mental status, bacteremia, septic shock, Acute Physiology and Chronic Health Evaluation (APACHE) II score, and Sequential Organ Failure Assessment (SOFA) score within the first 24 h; the highest temperature within 24 h after admission; mechanical ventilation usage; timing of antibiotic therapy; ICU stay; and 28-d survival were collected. Expression of mHLA-DR was measured by flow cytometry. RESULTS: APACHE II score and SOFA score were significantly higher (P < .001), whereas the mHLA-DR expression was significantly lower (P < .001) in the non-survivors than in the survivors. The outcomes at day 28 after admission were significantly associated with the APACHE II score (P = .002, odds ratio [OR] = 1.27, 95% CI 1.10-1.48), the SOFA score (P = .003, OR = 1.52, 95% CI 1.15-2.00), and mHLA-DR level (P = .01, OR = 0.91, 95% CI 0.85-0.98), as shown by logistic regression. The area under the receiver operating characteristic curve was 0.877 (95% CI 0.81-0.94, P < .001), 0.862 (95% CI 0.79-0.93, P < .001), and 0.781 (95% CI 0.69-0.87, P < .001) for APACHE II score, SOFA score, and the mHLA-DR expression, respectively. The optimal threshold for mHLA-DR level was 27.2%. Kaplan-Meier survival analysis showed that subjects with mHLA-DR ≥ 27.2% had significantly better outcomes compared with < 27.2% level (P < .001, log rank test, hazard ratio = 0.963, 95% CI 0.94-0.99). CONCLUSIONS: mHLA-DR may be a reliable biomarker that can predict the outcomes of patients with severe community-acquired pneumonia, and 27.2% may be the cut-off value to predict the outcomes.