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. Visual Abstract

Full Monte Carlo (MC)-based SPECT reconstructions have a strong potential for correcting for image degrading factors, but the reconstruction times are long. The objective of this study was to develop a highly parallel Monte Carlo code for fast, ordered subset expectation maximum (OSEM) reconstructions of SPECT/CT images. The MC code was written in the Compute Unified Device Architecture language for a computer with four graphics processing units (GPUs) (GeForce GTX Titan X, Nvidia, USA). This enabled simulations of parallel photon emissions from the voxels matrix (1283 or 2563). Each computed tomography (CT) number was converted to attenuation coefficients for photo absorption, coherent scattering, and incoherent scattering. For photon scattering, the deflection angle was determined by the differential scattering cross sections. An angular response function was developed and used to model the accepted angles for photon interaction with the crystal, and a detector scattering kernel was used for modeling the photon scattering in the detector. Predefined energy and spatial resolution kernels for the crystal were used. The MC code was implemented in the OSEM reconstruction of clinical and phantom 177Lu SPECT/CT images. The Jaszczak image quality phantom was used to evaluate the performance of the MC reconstruction in comparison with attenuated corrected (AC) OSEM reconstructions and attenuated corrected OSEM reconstructions with resolution recovery corrections (RRC). The performance of the MC code was 3200 million photons/s. The required number of photons emitted per voxel to obtain a sufficiently low noise level in the simulated image was 200 for a 1283 voxel matrix. With this number of emitted photons/voxel, the MC-based OSEM reconstruction with ten subsets was performed within 20 s/iteration. The images converged after around six iterations. Therefore, the reconstruction time was around 3 min. The activity recovery for the spheres in the Jaszczak phantom was clearly improved with MC-based OSEM reconstruction, e.g., the activity recovery was 88% for the largest sphere, while it was 66% for AC-OSEM and 79% for RRC-OSEM. The GPU-based MC code generated an MC-based SPECT/CT reconstruction within a few minutes, and reconstructed patient images of 177Lu-DOTATATE treatments revealed clearly improved resolution and contrast.

The aim of this study was to analyze the required absorbed doses to detectable metastases (D_req) when using radionuclides with prostate specific membrane antigen (PSMA)-targeting radioligands to achieve a high probability for metastatic control. The Monte Carlo based analysis was performed for the clinically-used radionuclides yttrium-90, iodine-131, lutetium-177, and actinium-225, and the newly-proposed low-energy electron emitter terbium-161. It was demonstrated that metastatic formation rate highly influenced the metastatic distribution. Lower values generated few large detectable metastases, as in the case with oligo metastases, while high values generated a distribution of multiple small detectable metastases, as observed in patients with diffused visualized metastases. With equal number of detectable metastases, the total metastatic volume burden was 4–6 times higher in the oligo metastatic scenario compared to the diffusely visualized scenario. The D_req was around 30% higher for the situations with 20 detectable metastases compared to one detectable metastasis. The D_req for iodine-131 and yttrium-90 was high (920–3300 Gy). The D_req for lutetium-177 was between 560 and 780 Gy and considerably lower D_req were obtained for actinium-225 and terbium-161, with 240–330 Gy and 210–280 Gy, respectively. In conclusion, the simulations demonstrated that terbium-161 has the potential for being a more effective targeted radionuclide therapy for metastases using PSMA ligands.

Targeted radionuclide therapy with ¹⁷⁷Lu- and ⁹⁰Y-labeled radioconjugates is a clinically-established treatment modality for metastasized cancer. ⁴⁷Sc is a therapeutic radionuclide that decays with a half-life of 3.35 days and emits medium-energy β⁻-particles. In this study, ⁴⁷Sc was investigated, in combination with a DOTA-folate conjugate, and compared to the therapeutic properties of ¹⁷⁷Lu-folate and ⁹⁰Y-folate, respectively. In vitro, ⁴⁷Sc-folate demonstrated effective reduction of folate receptor-positive ovarian tumor cell viability similar to ¹⁷⁷Lu-folate, but ⁹⁰Y-folate was more potent at equal activities due to the higher energy of emitted β⁻-particles. Comparable tumor growth inhibition was observed in mice that obtained the same estimated absorbed tumor dose (~21 Gy) when treated with ⁴⁷Sc-folate (12.5 MBq), ¹⁷⁷Lu-folate (10 MBq), and ⁹⁰Y-folate (5 MBq), respectively. The treatment resulted in increased median survival of 39, 43, and 41 days, respectively, as compared to 26 days in untreated controls. There were no statistically significant differences among the therapeutic effects observed in treated groups. Histological assessment revealed no severe side effects two weeks after application of the radiofolates, even at double the activity used for therapy. Based on the decay properties and our results, ⁴⁷Sc is likely to be comparable to ¹⁷⁷Lu when employed for targeted radionuclide therapy. It may, therefore, have potential for clinical translation and be of particular interest in tandem with ⁴⁴Sc or ⁴³Sc as a diagnostic match, enabling the realization of radiotheragnostics in future.

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.

Low uptake ratios, high noise, poor resolution, and low contrast all combine to make the detection of neuroendocrine liver tumours by 111In-octreotide single photon emission tomography (SPECT) imaging a challenge. The aim of this study was to develop a segmentation analysis method that could improve the accuracy of hepatic neuroendocrine tumour detection. Our novel segmentation was benchmarked by a retrospective analysis of patients categorized as either 111In-octreotide positive (111In-octreotide(+)) or 111In-octreotide negative (111In-octreotide(−)) for liver tumours. Following a 3-year follow-up period, involving multiple imaging modalities, we further segregated 111In-octreotide-negative patients into two groups: one with no confirmed liver tumours (111In-octreotide(−)/radtech(−)) and the other, now diagnosed with liver tumours (111In-octreotide(−)/radtech(+)). We retrospectively applied our segmentation analysis to see if it could have detected these previously missed tumours using 111In-octreotide. Our methodology subdivided the liver and determined normalized numbers of uptake foci (nNUF), at various threshold values, using a connected-component labelling algorithm. Plots of nNUF against the threshold index (ThI) were generated. ThI was defined as follows: ThI = (c max − c thr)/c max, where c max is the maximal threshold value for obtaining at least one, two voxel sized, uptake focus; c thr is the voxel threshold value. The maximal divergence between the nNUF values for 111In-octreotide(−)/radtech(−), and 111In-octreotide(+) livers, was used as the optimal nNUF value for tumour detection. We also corrected for any influence of the mean activity concentration on ThI. The nNUF versus ThI method (nNUFTI) was then used to reanalyze the 111In-octreotide(−)/radtech(−) and 111In-octreotide(−)/radtech(+) groups. Of a total of 53 111In-octreotide(−) patients, 40 were categorized as 111In-octreotide(−)/radtech(−) and 13 as 111In-octreotide(−)/radtech(+) group. Optimal separation of the nNUF values for 111In-octreotide(−)/radtech(−) and 111In-octreotide(+) groups was defined at the nNUF value of 0.25, to the right of the bell shaped nNUFTI curve. ThIs at this nNUF value were dependent on the mean activity concentration and therefore normalized to generate nThI; a significant difference in nThI values was found between the 111In-octreotide(−)/radtech(−) and the 111In-octreotide(−)/radtech(+) groups (P < 0.01). As a result, four of the 13 111In-octreotide(−)/radtech(+) livers were redesigned as 111In-octreotide(+). The nNUFTI method has the potential to improve the diagnosis of liver tumours using 111In-octreotide.