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A deep neural network for fast and accurate scatter estimation in quantitative SPECT/CT under challenging scatter conditions.

ABSTRACT: PURPOSE:A major challenge for accurate quantitative SPECT imaging of some radionuclides is the inadequacy of simple energy window-based scatter estimation methods, widely available on clinic systems. A deep learning approach for SPECT/CT scatter estimation is investigated as an alternative to computationally expensive Monte Carlo (MC) methods for challenging SPECT radionuclides, such as ⁹⁰Y. METHODS:A deep convolutional neural network (DCNN) was trained to separately estimate each scatter projection from the measured ⁹⁰Y bremsstrahlung SPECT emission projection and CT attenuation projection that form the network inputs. The 13-layer deep architecture consisted of separate paths for the emission and attenuation projection that are concatenated before the final convolution steps. The training label consisted of MC-generated "true" scatter projections in phantoms (MC is needed only for training) with the mean square difference relative to the model output serving as the loss function. The test data set included a simulated sphere phantom with a lung insert, measurements of a liver phantom, and patients after ⁹⁰Y radioembolization. OS-EM SPECT reconstruction without scatter correction (NO-SC), with the true scatter (TRUE-SC) (available for simulated data only), with the DCNN estimated scatter (DCNN-SC), and with a previously developed MC scatter model (MC-SC) were compared, including with ⁹⁰Y PET when available. RESULTS:The contrast recovery (CR) vs. noise and lung insert residual error vs. noise curves for images reconstructed with DCNN-SC and MC-SC estimates were similar. At the same noise level of 10% (across multiple realizations), the average sphere CR was 24%, 52%, 55%, and 67% for NO-SC, MC-SC, DCNN-SC, and TRUE-SC, respectively. For the liver phantom, the average CR for liver inserts were 32%, 73%, and 65% for NO-SC, MC-SC, and DCNN-SC, respectively while the corresponding values for average contrast-to-noise ratio (visibility index) in low-concentration extra-hepatic inserts were 2, 19, and 61, respectively. In patients, there was high concordance between lesion-to-liver uptake ratios for SPECT reconstruction with DCNN-SC (median 4.8, range 0.02-13.8) compared with MC-SC (median 4.0, range 0.13-12.1; CCC?=?0.98) and with ⁹⁰Y PET (median 4.9, range 0.02-11.2; CCC?=?0.96) while the concordance with NO-SC was poor (median 2.8, range 0.3-7.2; CCC?=?0.59). The trained DCNN took ~?40 s (using a single i5 processor on a desktop computer) to generate the scatter estimates for all 128 views in a patient scan, compared to ~?80 min for the MC scatter model using 12 processors. CONCLUSIONS:For diverse ⁹⁰Y test data that included patient studies, we demonstrated comparable performance between images reconstructed with deep learning and MC-based scatter estimates using metrics relevant for dosimetry and for safety. This approach that can be generalized to other radionuclides by changing the training data is well suited for real-time clinical use because of the high speed, orders of magnitude faster than MC, while maintaining high accuracy.

SUBMITTER: Xiang H

PROVIDER: S-EPMC7666660 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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A deep neural network for fast and accurate scatter estimation in quantitative SPECT/CT under challenging scatter conditions.

Xiang Haowei H Lim Hongki H Fessler Jeffrey A JA Dewaraja Yuni K YK

European journal of nuclear medicine and molecular imaging 20200515 13

<h4>Purpose</h4>A major challenge for accurate quantitative SPECT imaging of some radionuclides is the inadequacy of simple energy window-based scatter estimation methods, widely available on clinic systems. A deep learning approach for SPECT/CT scatter estimation is investigated as an alternative to computationally expensive Monte Carlo (MC) methods for challenging SPECT radionuclides, such as <sup>90</sup>Y.<h4>Methods</h4>A deep convolutional neural network (DCNN) was trained to separately es ...[more]

PMID: 32415551

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Project description:PURPOSE:In 90 Y microsphere radioembolization (RE), accurate post-therapy imaging-based dosimetry is important for establishing absorbed dose versus outcome relationships for developing future treatment planning strategies. Additionally, accurately assessing microsphere distributions is important because of concerns for unexpected activity deposition outside the liver. Quantitative 90 Y imaging by either SPECT or PET is challenging. In 90 Y SPECT model based methods are necessary for scatter correction because energy window-based methods are not feasible with the continuous bremsstrahlung energy spectrum. The objective of this work was to implement and evaluate a scatter estimation method for accurate 90 Y bremsstrahlung SPECT/CT imaging. METHODS:Since a fully Monte Carlo (MC) approach to 90 Y SPECT reconstruction is computationally very demanding, in the present study the scatter estimate generated by a MC simulator was combined with an analytical projector in the 3D OS-EM reconstruction model. A single window (105 to 195-keV) was used for both the acquisition and the projector modeling. A liver/lung torso phantom with intrahepatic lesions and low-uptake extrahepatic objects was imaged to evaluate SPECT/CT reconstruction without and with scatter correction. Clinical application was demonstrated by applying the reconstruction approach to five patients treated with RE to determine lesion and normal liver activity concentrations using a (liver) relative calibration. RESULTS:There was convergence of the scatter estimate after just two updates, greatly reducing computational requirements. In the phantom study, compared with reconstruction without scatter correction, with MC scatter modeling there was substantial improvement in activity recovery in intrahepatic lesions (from > 55% to > 86%), normal liver (from 113% to 104%), and lungs (from 227% to 104%) with only a small degradation in noise (13% vs. 17%). Similarly, with scatter modeling contrast improved substantially both visually and in terms of a detectability index, which was especially relevant for the low uptake extrahepatic objects. The trends observed for the phantom were also seen in the patient studies where lesion activity concentrations and lesion-to-liver concentration ratios were lower for SPECT without scatter correction compared with reconstruction with just two MC scatter updates: in eleven lesions the mean uptake was 4.9 vs. 7.1 MBq/mL (P = 0.0547), the mean normal liver uptake was 1.6 vs. 1.5 MBq/mL (P = 0.056) and the mean lesion-to-liver uptake ratio was 2.7 vs. 4.3 (P = 0.0402) for reconstruction without and with scatter correction respectively. CONCLUSIONS:Quantitative accuracy of 90 Y bremsstrahlung imaging can be substantially improved with MC scatter modeling without significant degradation in image noise or intensive computational requirements.

Project description:BackgroundThe introduction of hybrid SPECT/CT devices enables quantitative imaging in SPECT, providing a methodological setup for quantitation using SPECT tracers comparable to PET/CT. We evaluated a specific quantitative reconstruction algorithm for SPECT data using a 99mTc-filled NEMA phantom. Quantitative and qualitative image parameters were evaluated for different parametrizations of the acquisition and reconstruction protocol to identify an optimized quantitative protocol.ResultsThe reconstructed activity concentration (ACrec) and the signal-to-noise ratio (SNR) of all examined protocols (n = 16) were significantly affected by the parametrization of the weighting factor k used in scatter correction, the total number of iterations and the sphere volume (all, p < 0.0001). The two examined SPECT acquisition protocols (with 60 or 120 projections) had a minor impact on the ACrec and no significant impact on the SNR. In comparison to the known AC, the use of default scatter correction (k = 0.47) or object-specific scatter correction (k = 0.18) resulted in an underestimation of ACrec in the largest sphere volume (26.5 ml) by - 13.9 kBq/ml (- 16.3%) and - 7.1 kBq/ml (- 8.4%), respectively. An increase in total iterations leads to an increase in estimated AC and a decrease in SNR. The mean difference between ACrec and known AC decreased with an increasing number of total iterations (e.g., for 20 iterations (2 iterations/10 subsets) = - 14.6 kBq/ml (- 17.1%), 240 iterations (24i/10s) = - 8.0 kBq/ml (- 9.4%), p < 0.0001). In parallel, the mean SNR decreased significantly from 2i/10s to 24i/10s by 76% (p < 0.0001).ConclusionQuantitative SPECT imaging is feasible with the used reconstruction algorithm and hybrid SPECT/CT, and its consistent implementation in diagnostics may provide perspectives for quantification in routine clinical practice (e.g., assessment of bone metabolism). When combining quantitative analysis and diagnostic imaging, we recommend using two different reconstruction protocols with task-specific optimized setups (quantitative vs. qualitative reconstruction). Furthermore, individual scatter correction significantly improves both quantitative and qualitative results.

Project description:BackgroundLead-212 (212Pb) is a promising radionuclide for targeted therapy, as it decays to α-particle emitter bismuth-212 (212Bi) via β-particle emission. This extends the problematic short half-life of 212Bi. In preparation for upcoming clinical trials with 212Pb, the feasibility of quantitative single photon-emission computed tomography/computed tomography (SPECT/CT) imaging of 212Pb was studied, with the purpose to explore the possibility of individualised patient dosimetric estimation.ResultsBoth acquisition parameters (combining two different energy windows and two different collimators) and iterative reconstruction parameters (varying the iterations x subsets between 10 × 1, 15 × 1, 30 × 1, 30 × 2, 30 × 3, 30 × 4, and 30 × 30) were investigated to evaluate visual quality and quantitative uncertainties based on phantom images. Calibration factors were determined using a homogeneous phantom and were stable when the total activity imaged exceeded 1 MBq for all the imaging protocols studied, but they increased sharply as the activity decayed below 1 MBq. Both a 20% window centred on 239 keV and a 40% window on 79 keV, with dual scatter windows of 5% and 20%, respectively, could be used. Visual quality at the lowest activity concentrations was improved with the High Energy collimator and the 79 keV energy window. Fractional uncertainty in the activity quantitation, including uncertainties from calibration factors and small volume effects, in spheres of 2.6 ml in the NEMA phantom was 16-21% for all protocols with the 30 × 4 filtered reconstruction except the High Energy collimator with the 239 keV energy window. Quantitative analysis was possible both with and without filters, but the visual quality of the images improved with a filter.ConclusionsOnly minor differences were observed between the imaging protocols which were all determined suitable for quantitative imaging of 212Pb. As uncertainties generally decreased with increasing iterative updates in the reconstruction and recovery curves did not converge with few iterations, a high number of reconstruction updates are recommended for quantitative imaging.

Project description:A well-established approach for diagnostic imaging of osteomyelitis (OM), a bone infection, is simultaneous SPECT-CT of 99mTc sulfur colloid (SC) and 111In white blood cells (WBC). This method provides essentially perfect spatial registration of the tracers within anatomic sites of interest. Currently, diagnosis is based purely on a visual assessment-where relative discordance between 99mTc and 111In uptake in bone, i.e., high 111In and low 99mTc, suggests OM. To achieve more quantitative images, noise, scatter, and crosstalk between radionuclides must be addressed through reconstruction. Here the authors compare their Monte Carlo-based joint OSEM (MC-JOSEM) algorithm, which reconstructs both radionuclides simultaneously, to a more conventional triple-energy window-based reconstruction (TEW-OSEM), and to iterative reconstruction with no compensation for scatter (NC-OSEM).The authors created numerical phantoms of the foot and torso. Multiple bone-infection sites were modeled using high-count Monte Carlo simulation. Counts per voxel were then scaled to values appropriate for 111In WBC and 99mTc SC imaging. Ten independent noisy projection image sets were generated by drawing random Poisson deviates from these very low-noise images. Data were reconstructed using the two iterative scatter-compensation methods, TEW-OSEM and MC-JOSEM, as well as the uncorrected method (NC-OSEM). Mean counts in volumes of interest (VOIs) were used to evaluate the bias and precision of each method. Data were also acquired using a phantom, approximately the size of an adult ankle, consisting of regions representing infected and normal bone marrow, within a bone-like attenuator and surrounding soft tissue; each compartment contained a mixture of 111In and 99mTc. Low-noise data were acquired during multiple short scans over 29 h on a Siemens Symbia T6 SPECT-CT with medium-energy collimators. Pure 99mTc and 111In projection datasets were derived by fitting the acquired projections to the sum of 99mTc and 111In contributions, using the known half-lives. Uncontaminated data were scaled and recombined into six datasets with different activity ratios; ten Poisson noise realizations were then generated for each ratio. VOIs in each of the compartments were used to evaluate the bias and precision of each method with respect to reconstructions of uncontaminated datasets. In addition to the simulated and acquired phantom images, the authors reconstructed patient images with MC-JOSEM and TEW-OSEM. Patient reconstructions were assessed qualitatively for lesion contrast, spatial definition, and scatter.For all simulated and acquired infection phantoms, the root-mean squared-error of measured 99mTc activity was significantly improved with MC-JOSEM and TEW-OSEM in comparison to NC-OSEM reconstructions. While MC-JOSEM trended toward outperforming TEW-OSEM, the improvement was only found to be significant (p<0.001) for the acquired bone phantom in which a wide range of 111In∕99mTc concentration ratios were tested. In all cases, scatter correction did not significantly improve 111In quantitation.Compensation for scatter and crosstalk is useful for improving quality, bias, and precision of 99mTc activity estimates in simultaneous dual-radionuclide imaging of OM. The use of the more rigorous MC-based estimates provided marginal improvements over TEW. While the phantom results were encouraging, more subjects are needed to evaluate the usefulness of quantitative 111In∕99mTc SPECT-CT in the clinic.

Project description:BackgroundFour state-of-the-art single-photon emission computed tomography-computed tomography (SPECT-CT) systems, namely Philips Brightview, General Electric Discovery NM/CT 670 and Infinia Hawkeye 4, and Siemens Symbia T6, were investigated in terms of accuracy of attenuation and scatter correction, contrast recovery for small hot and cold structures, and quantitative capabilities when using their dedicated three-dimensional iterative reconstruction with attenuation and scatter corrections and resolution recovery.MethodsThe National Electrical Manufacturers Association (NEMA) NU-2 1994 phantom with cold air, water, and Teflon inserts, and a homemade contrast phantom with hot and cold rods were filled with 99mTc and scanned. The acquisition parameters were chosen to provide adequate linear and angular sampling and high count statistics. The data were reconstructed using Philips Astonish, General Electric Evolution for Bone, or Siemens Flash3D, eight subsets, and a varying number of iterations. A procedure similar to the one used in positron emission tomography (PET) allowed us to obtain the factor to convert counts per pixel into activity per unit volume.ResultsEdge and oscillation artifacts were observed with all phantoms and all systems. At 30 iterations, the residual fraction in the inserts of the NEMA phantom fell below 3.5%. Contrast recovery increased with the number of iterations but became almost saturated at 24 iterations onwards. In the uniform part of the NEMA and contrast phantoms, a quantification error below 10% was achieved.ConclusionsIn objects whose dimensions exceeded the SPECT spatial resolution by several times, quantification seemed to be feasible within 10% error limits. A partial volume effect correction strategy remains necessary for the smallest structures. The reconstruction artifacts nevertheless remain a handicap on the road towards accurate quantification in SPECT and should be the focus of further works in reconstruction tomography.

Project description:AimsTafamidis treatment positively affects left ventricular (LV) structure and function and improves outcomes in patients with transthyretin amyloid cardiomyopathy (ATTR-CM). We aimed to investigate the relationship between treatment response and cardiac amyloid burden identified by serial quantitative 99mTc-DPD SPECT/CT. We furthermore aimed to identify nuclear imaging biomarkers that could be used to quantify and monitor response to tafamidis therapy.Methods and resultsForty wild-type ATTR-CM patients who underwent 99mTc-DPD scintigraphy and SPECT/CT imaging at baseline and after treatment with tafamidis 61 mg once daily [median, 9.0 months (interquartile range 7.0-10.0)] were divided into two cohorts based on the median (-32.3%) of the longitudinal percent change in standardized uptake value (SUV) retention index. ATTR-CM patients with a reduction greater than or equal to the median (n = 20) had a significant decrease in SUV retention index (P < 0.001) at follow-up, which translated into significant benefits in serum N-terminal prohormone of brain natriuretic peptide levels (P = 0.006), left atrial volume index (P = 0.038), as well as LV [LV global longitudinal strain: P = 0.028, LV ejection fraction (EF): P = 0.027, LV cardiac index (CI): P = 0.034] and right ventricular (RV) [RVEF: P = 0.025, RVCI: P = 0.048] functions compared with patients with a decrease less than the median (n = 20).ConclusionTreatment with tafamidis in ATTR-CM patients results in a significant reduction in SUV retention index, associated with significant benefits for LV and RV function and cardiac biomarkers. Serial quantitative 99mTc-DPD SPECT/CT imaging with SUV may be a valid tool to quantify and monitor response to tafamidis treatment in affected patients.Translational perspective99mTc-DPD SPECT/CT imaging with determination of SUV retention index as part of a routine annual examination can provide evidence of treatment response in ATTR-CM patients receiving disease-modifying therapy. Further long-term studies with 99mTc-DPD SPECT/CT imaging may help to evaluate the relationship between tafamidis-induced reduction in SUV retention index and outcome in patients with ATTR-CM and will demonstrate whether highly disease-specific 99mTc-DPD SPECT/CT imaging is more sensitive than routine diagnostic monitoring.

Dataset Information

A deep neural network for fast and accurate scatter estimation in quantitative SPECT/CT under challenging scatter conditions.

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A deep neural network for fast and accurate scatter estimation in quantitative SPECT/CT under challenging scatter conditions.

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