Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved 177Lu images

Improvements of 177Lu SPECT images from sparsely acquired projections by reconstruction with deep-learning-generated synthetic projections

BACKGROUND

For dosimetry, the demand for whole-body SPECT/CT imaging, which require long acquisition durations with dual-head Anger cameras, is increasing. Here we evaluated sparsely acquired projections and assessed whether the addition of deep-learning-generated synthetic intermediate projections (SIPs) could improve the image quality while preserving dosimetric accuracy.

METHODS

This study included 16 patients treated with 177Lu-DOTATATE with SPECT/CT imaging (120 projections, 120P) at four time points. Deep neural networks (CUSIPs) were designed and trained to compile 90 SIPs from 30 acquired projections (30P). The 120P, 30P, and three different CUSIP sets (30P + 90 SIPs) were reconstructed using Monte Carlo-based OSEM reconstruction (yielding 120P_rec, 30P_rec, and CUSIP_recs). The noise levels were visually compared. Quantitative measures of normalised root mean square error, normalised mean absolute error, peak signal-to-noise ratio, and structural similarity were evaluated, and kidney and bone marrow absorbed doses were estimated for each reconstruction set.

RESULTS

The use of SIPs visually improved noise levels. All quantitative measures demonstrated high similarity between CUSIP sets and 120P. Linear regression showed nearly perfect concordance of the kidney and bone marrow absorbed doses for all reconstruction sets, compared to the doses of 120P_rec (R2 ≥ 0.97). Compared to 120P_rec, the mean relative difference in kidney absorbed dose, for all reconstruction sets, was within 3%. For bone marrow absorbed doses, there was a higher dissipation in relative differences, and CUSIP_recs outperformed 30P_rec in mean relative difference (within 4% compared to 9%). Kidney and bone marrow absorbed doses for 30P_rec were statistically significantly different from those of 120_rec, as opposed to the absorbed doses of the best performing CUSIP_rec, where no statistically significant difference was found.

CONCLUSION

When performing SPECT/CT reconstruction, the use of SIPs can substantially reduce acquisition durations in SPECT/CT imaging, enabling acquisition of multiple fields of view of high image quality with satisfactory dosimetric accuracy.

[161Tb]Tb-PSMA-617 radioligand therapy in patients with mCRPC: preliminary dosimetry results and intra-individual head-to-head comparison to [177Lu]Lu-PSMA-617

Rationale: Evaluation of alternative radionuclides for use in prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) is currently focusing on 161Tb, which may provide advantages by emitting additional Auger and conversion electrons. In this pilot study, we present preliminary dosimetry data for [161Tb]Tb-PSMA-617 RLT in a direct comparison with [177Lu]Lu-PSMA-617. Method: Six patients with metastatic castration-resistant prostate cancer (mCRPC) underwent treatment with [177Lu]Lu-PSMA-617 and subsequently - after inadequate response - with [161Tb]Tb-PSMA-617. Whole-body planar and SPECT imaging-based dosimetry of organs at risk (kidneys and salivary glands) and tumor lesions were calculated using IDAC for 177Lu and OLINDA/EXM for 161Tb. The therapeutic index (TI) of mean tumor-absorbed doses over relevant organs at risk was calculated. Results: Mean absorbed doses to organs at risk of PSMA-RLT were slightly higher for [161Tb]Tb-PSMA-617 compared to [177Lu]Lu-PSMA-617 (kidneys: 0.643 ± 0.247 vs. 0.545 ± 0.231 Gy/GBq, factor 1.18; parotid gland: 0.367 ± 0.198 vs. 0.329 ± 0.180 Gy/GBq, factor 1.10), but markedly higher regarding tumor lesions (6.10 ± 6.59 vs 2.59 ± 3.30 Gy/GBq, factor 2.40, p < 0.001). Consequently, the mean TI was higher for [161Tb]Tb-PSMA-617 compared to [177Lu]Lu-PSMA-617 for both, the kidneys (11.54 ± 9.74 vs. 5.28 ± 5.13, p = 0.002) and the parotid gland (16.77 ± 13.10 vs. 12.51 ± 18.09, p = 0.008). Conclusion: In this intra-individual head-to-head pilot study, [161Tb]Tb-PSMA-617 delivered higher tumor-absorbed doses and resulted in superior TI compared to [177Lu]Lu-PSMA-617. This preliminary data support 161Tb as a promising radionuclide for PSMA-RLT in mCRPC.

Comparison of Otsu and an adapted Chan-Vese method to determine thyroid active volume using Monte Carlo generated SPECT images

BACKGROUND

The Otsu method and the Chan-Vese model are two methods proven to perform well in determining volumes of different organs and specific tissue fractions. This study aimed to compare the performance of the two methods regarding segmentation of active thyroid gland volumes, reflecting different clinical settings by varying the parameters: gland size, gland activity concentration, background activity concentration and gland activity concentration heterogeneity.

METHODS

A computed tomography was performed on three playdough thyroid phantoms with volumes 20, 35 and 50 ml. The image data were separated into playdough and water based on Hounsfield values. Sixty single photon emission computed tomography (SPECT) projections were simulated by Monte Carlo method with isotope Technetium-99 m ([Formula: see text]Tc). Linear combinations of SPECT images were made, generating 12 different combinations of volume and background: each with both homogeneous thyroid activity concentration and three hotspots of different relative activity concentrations (48 SPECT images in total). The relative background levels chosen were 5 %, 10 %, 15 % and 20 % of the phantom activity concentration and the hotspot activities were 100 % (homogeneous case) 150 %, 200 % and 250 %. Poisson noise, (coefficient of variation of 0.8 at a 20 % background level, scattering excluded), was added before reconstruction was done with the Monte Carlo-based SPECT reconstruction algorithm Sahlgrenska Academy reconstruction code (SARec). Two different segmentation algorithms were applied: Otsu's threshold selection method and an adaptation of the Chan-Vese model for active contours without edges; the results were evaluated concerning relative volume, mean absolute error and standard deviation per thyroid volume, as well as dice similarity coefficient.

RESULTS

Both methods segment the images well and deviate similarly from the true volumes. They seem to slightly overestimate small volumes and underestimate large ones. Different background levels affect the two methods similarly as well. However, the Chan-Vese model deviates less and paired t-testing showed significant difference between distributions of dice similarity coefficients (p-value [Formula: see text]).

CONCLUSIONS

The investigations indicate that the Chan-Vese model performs better and is slightly more robust, while being more challenging to implement and use clinically. There is a trade-off between performance and user-friendliness.

Future trends for patient-specific dosimetry methodology in molecular radiotherapy

Molecular radiotherapy is rapidly expanding, and new radiotherapeutics are emerging. The majority of treatments is still performed using empirical fixed activities and not tailored for individual patients. Molecular radiotherapy dosimetry is often seen as a promising candidate that would allow personalisation of treatments as outcome should ultimately depend on the absorbed doses delivered and not the activities administered. The field of molecular radiotherapy dosimetry has made considerable progress towards the feasibility of routine clinical dosimetry with reasonably accurate absorbed-dose estimates for a range of molecular radiotherapy dosimetry applications. A range of challenges remain with respect to the accurate quantification, assessment of time-integrated activity and absorbed dose estimation. In this review, we summarise a range of technological and methodological advancements, mainly focussed on beta-emitting molecular radiotherapeutics, that aim to improve molecular radiotherapy dosimetry to achieve accurate, reproducible, and streamlined dosimetry. We describe how these new technologies can potentially improve the often time-consuming considered process of dosimetry and provide suggestions as to what further developments might be required.

Physics-Guided Deep Scatter Estimation by Weak Supervision for Quantitative SPECT

Accurate scatter estimation is important in quantitative SPECT for improving image contrast and accuracy. With a large number of photon histories, Monte-Carlo (MC) simulation can yield accurate scatter estimation, but is computationally expensive. Recent deep learning-based approaches can yield accurate scatter estimates quickly, yet full MC simulation is still required to generate scatter estimates as ground truth labels for all training data. Here we propose a physics-guided weakly supervised training framework for fast and accurate scatter estimation in quantitative SPECT by using a 100× shorter MC simulation as weak labels and enhancing them with deep neural networks. Our weakly supervised approach also allows quick fine-tuning of the trained network to any new test data for further improved performance with an additional short MC simulation (weak label) for patient-specific scatter modelling. Our method was trained with 18 XCAT phantoms with diverse anatomies / activities and then was evaluated on 6 XCAT phantoms, 4 realistic virtual patient phantoms, 1 torso phantom and 3 clinical scans from 2 patients for 177Lu SPECT with single / dual photopeaks (113, 208 keV). Our proposed weakly supervised method yielded comparable performance to the supervised counterpart in phantom experiments, but with significantly reduced computation in labeling. Our proposed method with patient-specific fine-tuning achieved more accurate scatter estimates than the supervised method in clinical scans. Our method with physics-guided weak supervision enables accurate deep scatter estimation in quantitative SPECT, while requiring much lower computation in labeling, enabling patient-specific fine-tuning capability in testing.

Specific Uptake in the Bone Marrow Causes High Absorbed Red Marrow Doses During [177Lu]Lu-DOTATATE Treatment

Bone marrow suppression is a common side effect after [177Lu]Lu-DOTATATE treatment of neuroendocrine neoplasms. Neuroendocrine neoplasms share expression of somatostatin receptor type 2 with CD34-positive hematopoietic progenitor cells, potentially leading to active uptake in the radiosensitive red marrow region where these cells are located. This study aimed to identify and quantify specific red marrow uptake using SPECT/CT images collected after the first treatment cycle. Methods: Seventeen patients diagnosed with neuroendocrine neoplasms were treated with [177Lu]Lu-DOTATATE. Seven of them had confirmed bone metastases. After the first treatment cycle, each patient went through 4 SPECT/CT imaging sessions 4, 24, 48, and 168 h after administration. Monte Carlo-based reconstructions were used to quantify activity concentrations in tumors and multiple skeletal sites presumed to house red marrow: the T9-L5 vertebrae and the ilium portion of the hip bones. The activity concentration from the descending aorta was used as input in a compartment model intended to establish a pure red marrow biodistribution by separating the nonspecific blood-based contribution from the specific activity concentration in red marrow. The biodistributions from the compartment model were used to perform red marrow dosimetry at each skeletal site. Results: Increased uptake of [177Lu]Lu-DOTATATE was observed in the T9-L5 vertebrae and hip bones in all 17 patients compared with activity concentrations in the aorta. The mean specific red marrow uptake was 49% (range, 0%-93%) higher than the nonspecific uptake. The median (±SD) total absorbed dose to the red marrow was 0.056 ± 0.023 Gy/GBq and 0.043 ± 0.022 Gy/GBq for the mean of all vertebrae and hip bones, respectively. The patients with bone metastases had an absorbed dose of 0.085 ± 0.046 Gy/GBq and 0.069 ± 0.033 Gy/GBq for the vertebrae and hip bones, respectively. The red marrow elimination phase was statistically slower in patients with fast tumor elimination, which is in line with transferrin transport of 177Lu back to the red marrow. Conclusion: Our results suggest that specific red marrow uptake of [177Lu]Lu-DOTATATE is in line with observations of somatostatin receptor type 2-expressing hematopoietic progenitor cells within the bone marrow. Blood-based dosimetry methods fail to account for the prolonged elimination of specific uptake and underestimate the absorbed dose to red marrow.

Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in 111In-octreotide SPECT imaging

BACKGROUND

Early cancer detection is crucial for patients' survival. The image quality in ¹¹¹In-octreotide SPECT imaging could be improved by using Monte Carlo (MC)-based reconstruction. The aim of this observational study was to determine the detection rate of simulated liver lesions for MC-based ordered subset expectation maximization (OSEM) reconstruction compared to conventional attenuation-corrected OSEM reconstruction.

METHODS

Thirty-seven SPECT/CT examinations with ¹¹¹In-octreotide were randomly selected. The inclusion criterion was no liver lesions at the time of examination and for the following 3 years. SPECT images of spheres representing lesions were simulated using MC. The raw data of the spheres were added to the raw data of the established healthy patients in 26 of the examinations, and the remaining 11 examinations were not modified. The images were reconstructed using conventional OSEM reconstruction with attenuation correction and post filtering (fAC OSEM) and MC-based OSEM reconstruction without and with post filtering (MC OSEM and fMC OSEM, respectively). The images were visually and blindly evaluated by a nuclear medicine specialist. The criteria evaluated were liver lesion yes or no, including coordinates if yes, with confidence level 1-3. The percentage of detected lesions and accuracy (percentage of correctly classified cases), as well as tumor-to-normal tissue concentration (TNC) ratios and signal-to-noise ratios (SNRs), were evaluated.

RESULTS

The detection rates were 30.8% for fAC OSEM, 42.3% for fMC OSEM, and 50.0% for MC OSEM. The accuracies were 45.9% for fAC OSEM, 45.9% for fMC OSEM, and 54.1% for MC OSEM. The number of false positives was higher for fMC and MC OSEM. The observer's confidence level was higher in filtered images than in unfiltered images. TNC ratios were significantly higher, statistically, with MC OSEM and fMC OSEM than with AC OSEM, but SNRs were similar due to higher noise with MC OSEM.

CONCLUSION

One in two lesions were found using MC OSEM versus one in three using conventional reconstruction. TNC ratios were significantly improved, statistically, using MC-based reconstruction, but the noise levels increased and consequently the confidence level of the observer decreased. For further improvements, image noise needs to be suppressed.

Patient-specific dosimetry adapted to variable number of SPECT/CT time-points per cycle for [Formula: see text]Lu-DOTATATE therapy

BACKGROUND

The number of SPECT/CT time-points is important for accurate patient dose estimation in peptide receptor radionuclide therapy. However, it may be limited by the patient's health and logistical reasons. Here,  an image-based dosimetric workflow adapted to the number of SPECT/CT acquisitions available throughout the treatment cycles was proposed, taking into account patient-specific pharmacokinetics and usable in clinic for all organs at risk.

METHODS

Thirteen patients with neuroendocrine tumors were treated with four injections of 7.4 GBq of [Formula: see text]Lu-DOTATATE. Three SPECT/CT images were acquired during the first cycle (1H, 24H and 96H or 144H post-injection) and a single acquisition (24H) for following cycles. Absorbed doses were estimated for kidneys (LK and RK), liver (L), spleen (S), and three surrogates of bone marrow (L2 to L4, L1 to L5 and T9 to L5) that were compared. 3D dose rate distributions were computed with Monte Carlo simulations. Voxel dose rates were averaged at the organ level. The obtained Time Dose-Rate Curves (TDRC) were fitted with a tri-exponential model and time-integrated. This method modeled patient-specific uptake and clearance phases observed at cycle 1. Obtained fitting parameters were reused for the following cycles, scaled to the measure organ dose rate at 24H. An alternative methodology was proposed when some acquisitions were missing based on population average TDRC (named STP-Inter). Seven other patients with three SPECT/CT acquisitions at cycles 1 and 4 were included to estimate the uncertainty of the proposed methods.

RESULTS

Absorbed doses (in Gy) per cycle available were: 3.1 ± 1.1 (LK), 3.4 ± 1.5 (RK), 4.5 ± 2.8 (L), 4.6 ± 1.8 (S), 0.3 ± 0.2 (bone marrow). There was a significant difference between bone marrow surrogates (L2 to L4 and L1 to L5, Wilcoxon's test: p value < 0.05), and while depicting very doses, all three surrogates were significantly different than dose in background (p value < 0.01). At cycle 1, if the acquisition at 24H is missing and approximated, medians of percentages of dose difference (PDD) compared to the initial tri-exponential function were inferior to 3.3% for all organs. For cycles with one acquisition, the median errors were smaller with a late time-point. For STP-Inter, medians of PDD were inferior to 7.7% for all volumes, but it was shown to depend on the homogeneity of TDRC.

CONCLUSION

The proposed workflow allows the estimation of organ doses, including bone marrow, from a variable number of time-points acquisitions for patients treated with [Formula: see text]Lu-DOTATATE.

Radiometal-Labeled Chitosan Microspheres as Transarterial Radioembolization Agents against Hepatocellular Carcinoma

Transarterial radioembolization (TARE) is an emerging treatment for patients with unresectable hepatocellular carcinoma (HCC). This study successfully developed radiometal-labeled chitosan microspheres (111In/177Lu-DTPA-CMS) with a diameter of 36.5 ± 5.3 μm for TARE. The radiochemical yields of 111In/177Lu-DTPA-CMS were greater than 90% with high radiochemical purities (>98%). Most of the 111In/177Lu-DTPA-CMS were retained in the hepatoma and liver at 1 h after intraarterial (i.a.) administration. Except for liver accumulation, radioactivity in each normal organ was less than 1% of the injected radioactivity (%IA) at 72 h after injection. At 10 days after injection of 177Lu-DTPA-CMS (18.6 ± 1.3 MBq), the size of the hepatoma was significantly reduced by around 81%, while that of the rats in the control group continued to grow. This study demonstrated the effectiveness of 177Lu-DTPA-CMS in the treatment of N1-S1 hepatoma. 111In/177Lu-DTPA-CMS have the potential to be a superior theranostic pair for the treatment of clinical hepatoma.

Optimizing the Schedule of PARP Inhibitors in Combination with 177Lu-DOTATATE: A Dosimetry Rationale

¹⁷⁷Lu-DOTATATE for neuroendocrine tumours is considered a low-toxicity treatment and may therefore be combined with other pharmaceuticals to potentiate its efficacy. One approach is to add a poly-[ADP-ribose]-polymerase (PARP) inhibitor to decrease the ability of tumour cells to repair ¹⁷⁷Lu-induced DNA damage. To decrease the risk of side effects, the sequencing should be optimized according to the tumour-to-normal tissue enhanced dose ratio (TNED). The aim of this study was to investigate how to enhance ¹⁷⁷Lu-DOTATATE by optimal timing of the addition of a PARP inhibitor. Biokinetic modelling was performed based on the absorbed dose to the bone marrow, kidneys and tumour; determined from SPECT/CT and planar images from 17 patients treated with ¹⁷⁷Lu-DOTATATE. To investigate the theoretical enhanced biological effect of a PARP inhibitor during ¹⁷⁷Lu-DOTATATE treatment, the concept of relative biological effectiveness (RBE) was used, and PARP inhibitor administration was simulated over different time intervals. The absorbed dose rate for the tumour tissue demonstrated an initial increase phase until 12 h after infusion followed by a slow decrease. In contrast, the bone marrow showed a rapid initial dose rate decrease. Twenty-eight days after infusion of ¹⁷⁷Lu-DOTATATE, the full absorbed dose to the bone marrow and kidney was reached. Using an RBE value of 2 for both the tumour and normal tissues, the TNED was increased compared to ¹⁷⁷Lu-DOTATATE alone. According to the modelling, the PARP inhibitor should be introduced approximately 24 h after the start of ¹⁷⁷Lu-DOTATATE treatment and be continued for up to four weeks to optimize the TNED. Based on these results, a phase I trial assessing the combination of olaparib and ¹⁷⁷Lu-DOTATATE in somatostatin receptor-positive tumours was launched in 2020 (NCT04375267).

IMPROVEMENTS OF 111IN SPECT IMAGES RECONSTRUCTED WITH SPARSELY ACQUIRED PROJECTIONS BY DEEP LEARNING GENERATED SYNTHETIC PROJECTIONS

The aim was to improve single-photon emission computed tomography (SPECT) quality for sparsely acquired 111In projections by adding deep learning generated synthetic intermediate projections (SIPs). Method: The recently constructed deep convolutional network for generating synthetic intermediate projections (CUSIP) was used for improving 20 sparsely acquired 111In-octreotide SPECTs. Reconstruction was performed with 120 (120P) or 30 (30P) projections, or 120 projections with 90 SIPs generated from 30 projections (30-120SIP). The SPECT reconstructions were performed with attenuation, scatter and collimator response corrections. Postfiltered 30P reconstructed SPECT was also analyzed. Image quality were quantitatively evaluated with root-mean-square error, peak signal-to-noise ratio and structural similarity index metrics. Result: The 30-120SIP reconstructed SPECT had statistically significant improved image quality parameters compared to 30P reconstructed SPECT with and without post filtering. The images visual appearance was similar to slightly filtered 120P SPECTs. Thereby, substantial acquisition time reduction with SIPs seems possible without image quality degradation.

EVALUATION OF THE SPATIAL RESOLUTION IN MONTE CARLO-BASED SPECT/CT RECONSTRUCTION OF 111IN-OCTREOTIDE IMAGES

The purpose was to evaluate the spatial resolution in 111In-octreotide single-photom emission computed tomography (SPECT)/computed tomography (CT) imaging following reconstructions with three different ordered subset expectation maximizations (OSEM) reconstruction algorithms; attenuation corrected (AC) OSEM, AC OSEM with resolution recovery (ACRR OSEM) and Monte Carlo-based OSEM reconstruction (MC OSEM). SPECT/CT imaging of a triple line phantom containing 111In in air and water was performed. The spatial resolution, represented by the full width at half maximum (FWHM) of a line profile, was determined for each line, for X and Y direction and for all reconstructions. The mean FWHM was 12.2 mm (±standard deviation [SD] 3.7 mm) for AC OSEM, 9.3 mm (±SD 2.5 mm) for ACRR OSEM and 8.2 mm (±SD 2.0 mm) for MC OSEM. MC-based SPECT/CT reconstruction clearly improves the spatial resolution in 111In-octreotide imaging and since MC simulations can be performed for all photon energies MC OSEM has the potential to improve SPECT/CT imaging overall.

Renal and Red Marrow Dosimetry in Peptide Receptor Radionuclide Therapy: 20 Years of History and Ahead

The development of dosimetry and studies in peptide receptor radionuclide therapy (PRRT) over the past two decades are reviewed. Differences in kidney and bone marrow toxicity reported between ⁹⁰Y, ¹⁷⁷Lu and external beam radiotherapy (EBRT) are discussed with regard to the physical properties of these beta emitter radionuclides. The impact of these properties on the response to small and large tumors is also considered. Capacities of the imaging modalities to assess the dosimetry to target tissues are evaluated. Studies published in the past two years that confirm a red marrow uptake in ¹⁷⁷Lu-DOTATATE therapy, as already observed 20 years ago in ⁸⁶Y-DOTATOC PET studies, are analyzed in light of the recent developments in the transferrin transport mechanism. The review enlightens the importance (i) of using state-of-the-art imaging modalities, (ii) of individualizing the activity to be injected with regard to the huge tissue uptake variability observed between patients, (iii) of challenging the currently used but inappropriate blood-based red marrow dosimetry and (iv) of considering individual tandem therapy. Last, a smart individually optimized tandem therapy taking benefit of the bi-orthogonal toxicity-response pattern of ¹⁷⁷Lu-DOTATATE and of ⁹⁰Y-DOTATOC is proposed.

Artificial intelligence in single photon emission computed tomography (SPECT) imaging: a narrative review

Artificial intelligence (AI) has been widely applied to medical imaging. The use of AI for emission computed tomography, particularly single-photon emission computed tomography (SPECT) emerged nearly 30 years ago but has been accelerated in recent years due to the development of AI technology. In this review, we will describe and discuss the progress of AI technology in SPECT imaging. The applications of AI are dispersed in disease prediction and diagnosis, post-reconstruction image denoising, attenuation map generation, and image reconstruction. These applications are relevant to many disease categories such as the neurological disorders, kidney failure, cancer, heart disease, etc. This review summarizes these applications so that SPECT researchers can have a reference overview of the role of AI in current SPECT studies. For each application, we followed the timeline to present the evolution of AI’s usage and offered insights on how AI was combined with the knowledge of underlying physics as well as traditional non-learning techniques. Ultimately, AI applications are critical to the progress of modern SPECT technology because they provide compensations for many deficiencies in conventional SPECT imaging methods and demonstrate unparalleled success. Nonetheless, AI also has its own challenges and limitations in the medical field, including SPECT imaging. These fundamental questions are discussed, and possible future directions and countermeasures are suggested.

Evaluation of SSTR2 Expression in SI-NETs and Relation to Overall Survival after PRRT

Simple Summary

Small intestinal neuroendocrine tumors (SI-NETs) are slow growing tumors expressing somatostatin receptors (SSTR), which are targeted in diagnostic and therapeutic methods. A fairly new treatment that targets SSTR2 is peptide receptor radionuclide therapy (PRRT), which prolongs survival for patients with metastasized NETs. However, the treatment is costly, and the effect is variable. Therefore, finding predictors for treatment response is warranted. The aim of this retrospective study was to immunohistochemically analyze the SSTR2 expression in SI-NETs, using a previously constructed tissue microarray, and to investigate if a high SSTR2 expression was correlated to overall survival (OS). Among 42 patients that had received PRRT, 10 had at least one tumor with low SSTR2 expression. The patients were grouped according to the SSTR2 expression (“High SSTR2” and “Low SSTR2”) in previously resected tumors. In contrast to the hypothesis of the study, patients with low SSTR2 expression had significantly longer OS after PRRT, compared with patients with high SSTR2 expression. Hence, the study suggests that low SSTR2 expression in resected tumors should not exclude SI-NET patients from receiving PRRT.

Abstract

(1) Purpose: Small intestinal neuroendocrine tumors (SI-NETs) often present with distant metastases at diagnosis. Peptide receptor radionuclide therapy (PRRT) with radiolabeled somatostatin analogues is a systemic treatment that increases overall survival (OS) in SI-NET patients with stage IV disease. However, the treatment response after PRRT, which targets somatostatin receptor 2 (SSTR2), is variable and predictive factors have not been established. This exploratory study aims to evaluate if SSTR2 expression in SI-NETs could be used to predict OS after PRRT treatment. (2) Methods: Using a previously constructed Tissue Micro Array (TMA) we identified tissue samples from 42 patients that had received PRRT treatment during 2006–2017 at Sahlgrenska University hospital. Immunohistochemical expression of SSTR2, Ki-67 and neuroendocrine markers synaptophysin and Chromogranin A (CgA) were assessed. A retrospective estimation of ¹⁷⁷Lu-DOTATATE uptake in 33 patients was performed. Data regarding OS and non-surgical treatment after PRRT were collected. Another subgroup of 34 patients with paired samples from 3 tumor sites (primary tumor, lymph node and liver metastases) was identified in the TMA. The SSTR2 expression was assessed in corresponding tissue samples (n = 102). (3) Results: The patients were grouped into Low SSTR2 or High SSTR2 groups based upon on levels of SSTR2 expression. There was no significant difference in ¹⁷⁷Lu-DOTATATE uptake between the groups. The patients in the Low SSTR2 group had significantly longer OS after PRRT than the patients in the High SSTR2 group (p = 0.049). PRRT treated patients with low SSTR2 expression received less additional treatment compared with patients with high SSTR2 expression. SSTR2 expression did not vary between tumor sites but correlated within patients. (4) Conclusion: The results from the present study suggest that retrospective evaluation of SSTR2 expression in resected tumors cannot be used to predict OS after PRRT.

Modeling complex particles phase space with GAN for Monte Carlo SPECT simulations: a proof of concept

A method is proposed to model by a generative adversarial network the distribution of particles exiting a patient during Monte Carlo simulation of emission tomography imaging devices. The resulting compact neural network is then able to generate particles exiting the patient, going towards the detectors, avoiding costly particle tracking within the patient. As a proof of concept, the method is evaluated for single photon emission computed tomography (SPECT) imaging and combined with another neural network modeling the detector response function (ARF-nn). A complete rotating SPECT acquisition can be simulated with reduced computation time compared to conventional Monte Carlo simulation. It also allows the user to perform simulations with several imaging systems or parameters, which is useful for imaging system design.

First-in-Humans Application of 161Tb: A Feasibility Study Using 161Tb-DOTATOC

¹⁶¹Tb has decay properties similar to those of ¹⁷⁷Lu but, additionally, emits a substantial number of conversion and Auger electrons. The aim of this study was to apply ¹⁶¹Tb in a clinical setting and to investigate the feasibility of visualizing the physiologic and tumor biodistributions of ¹⁶¹Tb-DOTATOC. Methods: ¹⁶¹Tb was shipped from Paul Scherrer Institute, Villigen-PSI, Switzerland, to Zentralklinik Bad Berka, Bad Berka, Germany, where it was used for the radiolabeling of DOTATOC. In 2 separate studies, 596 and 1,300 MBq of ¹⁶¹Tb-DOTATOC were administered to a 35-y-old male patient with a metastatic, well-differentiated, nonfunctional malignant paraganglioma and a 70-y-old male patient with a metastatic, functional neuroendocrine neoplasm of the pancreatic tail, respectively. Whole-body planar γ-scintigraphy images were acquired over a period of several days for dosimetry calculations. SPECT/CT images were reconstructed using a recently established protocol and visually analyzed. Patients were observed for adverse events after the application of ¹⁶¹Tb-DOTATOC. Results: The radiolabeling of DOTATOC with ¹⁶¹Tb was readily achieved with a high radiochemical purity suitable for patient application. Planar images and dosimetry provided the expected time-dependent biodistribution of ¹⁶¹Tb-DOTATOC in the liver, kidneys, spleen, and urinary bladder. SPECT/CT images were of high quality and visualized even small metastases in bones and liver. The application of ¹⁶¹Tb-DOTATOC was well tolerated, and no related adverse events were reported. Conclusion: This study demonstrated the feasibility of imaging even small metastases after the injection of relatively low activities of ¹⁶¹Tb-DOTATOC using γ-scintigraphy and SPECT/CT. On the basis of this essential first step in translating ¹⁶¹Tb to clinics, further efforts will be directed toward the application of ¹⁶¹Tb for therapeutic purposes.

Deep-Learning Generation of Synthetic Intermediate Projections Improves 177Lu SPECT Images Reconstructed with Sparsely Acquired Projections

The aims of this study were to decrease the ¹⁷⁷Lu-SPECT acquisition time by reducing the number of projections and to circumvent image degradation by adding deep-learning-generated synthesized projections. Methods: We constructed a deep convolutional U-net-shaped neural network for generation of synthetic intermediate projections (CUSIPs). The number of SPECT investigations was 352 for training, 37 for validation, and 15 for testing. The input was every fourth projection of 120 acquired SPECT projections, that is, 30 projections. The output was 30 synthetic intermediate projections (SIPs) per CUSIP. SPECT images were reconstructed with 120 or 30 projections, or with 120 projections when 90 SIPs were generated from 30 projections (30-120SIPs), using 3 CUSIPs. The reconstructions were performed with 2 ordered-subset expectation maximization (OSEM) algorithms: attenuation-corrected (AC) OSEM, and attenuation, scatter, and collimator response-corrected (ASCC) OSEM. The quality of the SIPs and SPECT images was quantitatively evaluated with root-mean-square error, peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) index metrics. From a Jaszczak SPECT phantom, the recovery and signal-to-noise ratio (SNR) were determined. In addition, an experienced observer qualitatively assessed the SPECT image quality of the test set. Kidney activity concentrations, as determined from the different SPECT images, were compared. Results: The generated SIPs had a mean SSIM value of 0.926 (SD, 0.061). For AC-OSEM, the reconstruction with 30-120SIPs had higher SSIM (0.993 vs. 0.989, P < 0.001) and PSNR (49.5 vs. 47.2, P < 0.001) values than the reconstruction with 30 projections. ASCC-OSEM had higher SSIM and PSNR values than AC-OSEM (P < 0.001). There was a minor loss in recovery for 30-120SIPs, but SNR was clearly improved compared with 30 projections. The observer assessed 27 of 30 images reconstructed with 30 projections as having unacceptable noise levels, whereas the corresponding values were 2 of 60 for 30-120SIPs and 120 projections. Image quality did not differ significantly between 30-120SIPs and 120 projections. The kidney activity concentration was similar between the different projection sets, excepting a minor reduction of 2.5% for ASCC-OSEM 30-120SIPs. Conclusion: Adopting SIPs for sparsely acquired projections considerably recovers image quality and could allow a reduced SPECT acquisition time in clinical dosimetry protocols.

Establishment of a clinical SPECT/CT protocol for imaging of 161Tb

Background

It has been proposed, and preclinically demonstrated, that ¹⁶¹Tb is a better alternative to ¹⁷⁷Lu for the treatment of small prostate cancer lesions due to its high emission of low-energy electrons. ¹⁶¹Tb also emits photons suitable for single-photon emission computed tomography (SPECT) imaging. This study aims to establish a SPECT protocol for ¹⁶¹Tb imaging in the clinic.

Materials and methods

Optimal settings using various γ-camera collimators and energy windows were explored by imaging a Jaszczak phantom, including hollow-sphere inserts, filled with ¹⁶¹Tb. The collimators examined were extended low-energy general purpose (ELEGP), medium-energy general purpose (MEGP), and low-energy high resolution (LEHR), respectively. In addition, three ordered subset expectation maximization (OSEM) algorithms were investigated: attenuation-corrected OSEM (A-OSEM); attenuation and dual- or triple-energy window scatter-corrected OSEM (AS-OSEM); and attenuation, scatter, and collimator-detector response-corrected OSEM (ASC-OSEM), where the latter utilized Monte Carlo-based reconstruction. Uniformity corrections, using intrinsic and extrinsic correction maps, were also investigated. Image quality was assessed by estimated recovery coefficients (RC), noise, and signal-to-noise ratio (SNR). Sensitivity was determined using a circular flat phantom.

Results

The best RC and SNR were obtained at an energy window between 67.1 and 82.1 keV. Ring artifacts, caused by non-uniformity, were removed with extrinsic uniformity correction for the energy window between 67.1 and 82.1 keV, but not with intrinsic correction. Analyzing the lower energy window between 48.9 and 62.9 keV, the ring artifacts remained after uniformity corrections. The recovery was similar for the different collimators when using a specific OSEM reconstruction. Recovery and SNR were highest for ASC-OSEM, followed by AS-OSEM and A-OSEM. When using the optimized parameter setting, the resolution of ¹⁶¹Tb was higher than for ¹⁷⁷Lu (8.4 ± 0.7 vs. 10.4 ± 0.6 mm, respectively). The sensitivities for ¹⁶¹Tb and ¹⁷⁷Lu were 7.41 and 8.46 cps/MBq, respectively.

Conclusion

SPECT with high resolution is feasible with ¹⁶¹Tb; however, extrinsic uniformity correction is recommended to avoid ring artifacts. The LEHR collimator was the best choice of the three tested to obtain a high-resolution image. Due to the complex emission spectrum of low-energy photons, window-based scatter correction had a minor impact on the image quality compared to using attenuation correction only. On the other hand, performing attenuation, scatter, and collimator-detector correction clearly improved image quality. Based on these data, SPECT-based dosimetry for ¹⁶¹Tb-labeled radiopharmaceuticals is feasible.

Adaptive scan duration in SPECT: Evaluation for radioembolization

PURPOSE

It may be challenging to select the optimal scan duration for single-photon emission computed tomography (SPECT) protocols because the activity distribution characteristics can differ in every scan. Using simulations and experiments, we investigated whether the scan duration can be optimized for every scan separately by evaluating the activity distribution during scanning. We refer to this as adaptive scanning.

METHODS

The feasibility of adaptive scanning was evaluated for the detection of extrahepatic depositions in the pretreatment procedure of radioembolization, in which ^99m Tc-labeled macroaggregated albumin (^99m Tc-MAA) is injected into the liver. We simulated fast 1-min detector rotations and updated the reconstruction with the newly collected counts after every rotation. The scan was terminated when one of the two criteria was met: (a) when the mask difference of the detected extrahepatic deposition between two consecutive rotations was lower than 5%; or (b) when the reconstructed extrahepatic activity was negligible with respect to the total reconstructed activity (<0.075%). The performance of adaptive scanning was evaluated using a digital phantom with various activity distributions, a physical phantom experiment, and simulations based on 129 patient activity distributions.

RESULTS

The digital phantom data showed that the scan termination times substantially depended on the activity distribution characteristics. The experimental phantom data showed the feasibility of adaptive scanning with physical scanner measurements and illustrated that fast detector motion was not limiting the adaptive scanning performance. The patient data showed a large spread in the scan terminations times. By adaptive scanning, the mean scan duration of the patient distributions was shortened from 20 min (current clinical protocol) to 4.8 ± 0.2 min. The detection accuracy of extrahepatic depositions was unaffected and the mean difference in the extrahepatic deposition masks (compared with the 20-min scan) was only 7.0 ± 1.0%.

CONCLUSION

Our study suggests that the SPECT scan duration can be personalized by assessing the activity distribution characteristics during scanning for the detection of extrahepatic depositions in the pretreatment procedure of radioembolization. The adaptive scanning approach might also be of benefit for other SPECT protocols, as long as a measure of interest is available for optimization.

Accelerated SPECT image reconstruction with FBP and an image enhancement convolutional neural network

BACKGROUND

Monte Carlo-based iterative reconstruction to correct for photon scatter and collimator effects has been proven to be superior over analytical correction schemes in single-photon emission computed tomography (SPECT/CT), but it is currently not commonly used in daily clinical practice due to the long associated reconstruction times. We propose to use a convolutional neural network (CNN) to upgrade fast filtered back projection (FBP) image quality so that reconstructions comparable in quality to the Monte Carlo-based reconstruction can be obtained within seconds.

RESULTS

A total of 128 technetium-99m macroaggregated albumin pre-treatment SPECT/CT scans used to guide hepatic radioembolization were available. Four reconstruction methods were compared: FBP, clinical reconstruction, Monte Carlo-based reconstruction, and the neural network approach. The CNN generated reconstructions in 5 sec, whereas clinical reconstruction took 5 min and the Monte Carlo-based reconstruction took 19 min. The mean squared error of the neural network approach in the validation set was between that of the Monte Carlo-based and clinical reconstruction, and the lung shunting fraction difference was lower than 2 percent point. A phantom experiment showed that quantitative measures required in radioembolization were accurately retrieved from the CNN-generated reconstructions.

CONCLUSIONS

FBP with an image enhancement neural network provides SPECT reconstructions with quality close to that obtained with Monte Carlo-based reconstruction within seconds.

Bone Marrow Absorbed Doses and Correlations with Hematologic Response During 177Lu-DOTATATE Treatments Are Influenced by Image-Based Dosimetry Method and Presence of Skeletal Metastases

This study aimed to compare different image-based methods for bone marrow dosimetry and study the dose–response relationship during treatment with ¹⁷⁷Lu-DOTATATE in patients with and without skeletal metastases. Methods: This study included 46 patients with advanced neuroendocrine tumors treated with at least 2 fractions of ¹⁷⁷Lu-DOTATATE at Sahlgrenska University Hospital. High- and low-uptake compartments were automatically outlined in planar images collected at 2, 24, 48, and 168 h after injection. The bone marrow absorbed doses were calculated from the cross doses of the high- and low-uptake compartments and the self-dose, using the time–activity concentration curve for the low-uptake compartment. This time–activity concentration curve was adjusted using a fixed constant of 1.8 for the planar dosimetry method and using the activity concentrations in vertebral bodies in SPECT images at 24 h after injection of ¹⁷⁷Lu-DOTATATE in 4 hybrid methods: L4-SPECT used the activity concentration in the L4 vertebra, whereas V-SPECT, L-SPECT, and T-SPECT used the median activity concentration in all visible vertebrae, lumbar vertebrae, and thoracic vertebrae, respectively. Results: Using the planar method, L4-SPECT, V-SPECT, L-SPECT, and T-SPECT, the estimated median bone marrow absorbed doses were 0.19, 0.36, 0.40, 0.39, and 0.46 Gy/7.4 GBq, respectively, with respective ranges of 0.12–0.33, 0.15–1.44, 0.19–1.71, 0.21–1.60, and 0.18–2.12 Gy/7.4 GBq. For all methods, the bone marrow absorbed dose significantly correlated with decreased platelet counts. This correlation increased after treatment fraction 2: the Spearman correlation (r_s) were −0.49 for the planar method, −0.61 for L4-SPECT, −0.63 for V-SPECT, −0.63 for L-SPECT, and −0.57 for T-SPECT. A separate analysis revealed an increased correlation for patients without skeletal metastases using the planar method (r_s = −0.67). In contrast, hybrid methods had poor correlations for patients without metastases and stronger correlations for patients with skeletal metastases (r_s = −0.61 to −0.74). The mean bone marrow absorbed doses were 3%–69% higher for patients with skeletal metastases than for patients without. Conclusion: The estimated bone marrow absorbed doses by image-based techniques and the correlation with platelets are influenced by the choice of measured vertebrae and the presence of skeletal metastases.

Monte Carlo-based SPECT reconstruction within the SIMIND framework

This paper presents the development and validation of a Monte Carlo-based singe photon emission computed tomography reconstruction program for parallel-hole collimation contained within the SIMIND Monte Carlo framework. The Monte Carlo code is used as an accurate forward-projector and is combined with a simplified back-projector to perform iterative tomographic reconstruction using the Maximum Likelihood Expectation Maximization and Ordered Subsets Expectation Maximization algorithms, together forming a program called SIMREC. The Monte Carlo simulation transforms the estimated source distribution directly from activity to counts in its projections. Hence, the reconstructed image is expressed in activity without reference to an external calibration. The program is tested using phantom measurements of spheres filled with ^99mTc, ¹⁷⁷Lu and ¹³¹I placed in air and centrally and peripherally in a water-filled elliptical phantom. The feasibility of applying the reconstruction to patients is also demonstrated for a range of radiopharmaceuticals. The deviation in total activity in the spheres ranged between  -4.1% and 6.2% compared with the activity determined when preparing the phantom. The SIMREC program was found to be accurate with respect to activity estimation and to reconstruct visually acceptable images within a few hours when applied to patient examples.