Abstract Objective. Crosstalk poses significant challenges in multi-radionuclide single-photon emission computed tomography (SPECT), where γ -rays from one radionuclide are incorrectly attributed to a different radionuclide, compromising image fidelity and interpretations. Although the triple energy window (TEW) method is widely accepted for correcting crosstalk in the acquired energy spectrum, its effectiveness depends on the gamma camera’s energy resolution and statistical counts on a pixel-by-pixel basis. Furthermore, subtractive corrections applied before image reconstruction, such as TEW, alter the Poisson distribution of detected events, negatively impacting statistical reconstruction accuracy, reconstructed image noise, and image quality. To address these challenges, we introduce an energy-based spectral unmixing crosstalk correction approach in a preclinical setting using the open-source Synergistic Image Reconstruction Framework and Core Imaging Library. This method employs a mixing matrix to decompose hyperspectral data into distinct radionuclide distributions during synergistic reconstruction. Approach. Data were acquired with the Cubresa Spark preclinical SPECT scanner using 99 m Tc/ 123 I in measurement and simulation, and 99 m Tc/ 111 In in simulation. A mouse-sized phantom study employed five 4 MBq line sources with linearly varying mixtures of radioactivity. The images were reconstructed using primary energy windows, TEW, spectral unmixing, and gold standard simulation data representing activity distributions free of crosstalk. Performance evaluation used root-mean-square error (RMSE) for activity quantitation and image contrast, while noise was assessed separately in each image. Main results. In the 99 m Tc/ 123 I measurement, primary energy windows yielded a mean quantitation RMSE of 0.49, with improvements of 32% observed with TEW and 74% with spectral unmixing. Simulation results were consistent, giving an RMSE of 0.44 for primary energy windows, with improvements of 51%, 83%, and 95% observed with TEW, spectral unmixing, and gold standard methods. For the 99 m Tc/ 111 In simulation, the mean quantitation RMSE was 0.15 with primary energy windows, while TEW, spectral unmixing, and gold standard methods improved accuracy by 57%, 57%, and 84%, respectively. Across all cases, spectral unmixing also demonstrated superior contrast and reduced noise compared to TEW. Significance. This energy-based spectral unmixing approach provides enhanced crosstalk correction, quantitative accuracy, and image quality compared to conventional methods, facilitating flexible application in diverse SPECT systems and radionuclide combinations.
Abstract Objective. Tumor stiffness has shown promise as a biomechanical marker of malignancy. However, many elastography studies model tumors as linear elastic materials, which may not fully capture the nonlinear behavior of soft tissue. This study developed and evaluated an inverse finite-element (FE) framework for estimating nonlinear tumor stiffness from standard B-mode ultrasound (US) images acquired during controlled compression. Approach. Synthetic B-mode images were generated from FE simulations of elliptical tumors embedded in healthy tissue. Three tumor aspect ratios were considered: α = 0.35 , 0.50 , and 0.75 . Both the tumor and surrounding tissue were modeled as nearly incompressible neo-Hookean materials. Tumor stiffness was assigned as 2 × , 4 × , or 6 × the background tissue stiffness, and three levels of compression were applied. Speckle tracking was used to estimate tissue displacements between the undeformed and compressed images. These displacement fields were then used in an inverse FE optimization. Two formulations were tested: one in which the background tissue stiffness was known and another in which both tumor and background stiffness were estimated. Main results. The inverse model closely reproduced the speckle-tracking (ST) displacement fields, with mean absolute errors below 0.01 mm for all cases. When the background tissue stiffness was known, tumor stiffness was estimated with R 2 > 0.98 . The average prediction errors were 2.57%, 2.90%, and 4.04% for α = 0.35 , 0.50 , and 0.75 , respectively, with a maximum error of 6.87%. However, estimating both stiffness parameters reduced accuracy because different tumor and tissue stiffness combinations could produce similar displacement patterns. Significance. These results demonstrate the feasibility of estimating nonlinear tumor stiffness from B-mode US-derived displacement fields using ST and inverse modeling in a controlled in silico setting. The study provides a computational framework for tumor stiffness estimation, with further methodological development needed to address segmentation, loading, and boundary-condition uncertainties before extending the approach beyond the controlled in silico setting.
Abstract Objective . To perform a comprehensive comparative analysis of proton, helium-ion, and carbon-ion computed tomography (CT) as direct imaging modalities for hadron therapy treatment planning, focusing on relative stopping power (RSP) reconstruction accuracy and patient radiation dose. Approach . High-fidelity Monte Carlo simulations were conducted using the GATE/Geant4 platform to model a standard CTP404 phantom. RSP maps were reconstructed using two iterative algorithms: the simultaneous algebraic reconstruction technique and the Richardson–Lucy deconvolution. Imaging performance was evaluated by comparing reconstructed RSP values against ground truth data for various tissue-equivalent inserts, while integral doses were estimated for a human head geometry using a Shepp–Logan-like phantom. Main results . All investigated particle modalities demonstrated a significant dose reduction compared to conventional x-ray CT protocols (which are approximately 40 mGy). The estimated imaging doses were 0.5 mGy for protons, 1.3 mGy for helium ions, and 7.5 mGy for carbon ions. In terms of accuracy, carbon-ion imaging achieved promising accuracy for soft-tissue materials (mean absolute error < 0.5 % ). Helium ions offered a balanced performance with sub- 1 % errors for most materials and a dose burden significantly lower than carbon ions. Protons exhibited the widest range of RSP deviations. Significance . Direct particle imaging eliminates the systematic uncertainties inherent in photon-to-hadron conversion, which typically introduce RSP deviations of 1.6%–3.5% in standard single-energy x-ray CT. While carbon ions provide better RSP reconstruction precision essential for complex treatment plans in heterogeneous anatomy, helium and proton imaging offer exceptional dose sparing, making them particularly advantageous for pediatric patients and frequent adaptive replanning scenarios.
Abstract Objective . Tellurium-118 ( 118 Te; t 1/2 = 6.00 ± 0.02 d) can act as an in vivo generator of the positron emitter antimony-118 ( 118 Sb; t 1/2 = 3.6 ± 0.3 min), enabling positron emission tomography (PET) over a week or longer. This work assessed absorbed doses associated with free 118 Te to establish a dosimetric safety basis for 118 Te radiopharmaceuticals. Approach . Injection solutions of free 118 Te were prepared by alpha-particle irradiation of an enriched tin-116 target followed by radiochemical isolation. Ex vivo biodistribution in healthy female Slc:ICR mice was acquired at seven time points from 2 h to 29 d postinjection ( n = 6 per time point). Time-integrated activity coefficients were computed from the biodistribution profiles and extrapolated to a human model using relative mass scaling. Absorbed dose coefficients (ADCs) were calculated following the medical internal radiation dose formalism with computational phantoms implemented in the dosimetry software OLINDA. Dosimetric contributions from 118 Te and its coproduced radioisotopic impurity 119m Te ( t 1/2 = 4.69 ± 0.04 d), along with their equilibrium daughters 118 Sb and 119 Sb, were individually assessed. Main results . The kidneys exhibited the highest ADC in both mouse (2666.0 mGy MBq −1 ) and human (2.639 mGy MBq −1 ) models. Bone received the second-highest ADC in the mouse model, 1855.5 mGy MBq −1 . Antimony-118 dominated absorbed doses across all organs examined, accounting for more than 82% of ADCs in both models. Contributions from 118 Te, 119m Te, and 119 Sb were minor by comparison. Significance . The kidneys and bone were identified as the primary dosimetric targets of free 118 Te, with its daughter 118 Sb being the principal dose contributor. The limited dosimetric impact from 118 Te provides justification for its use as an in vivo generator of 118 Sb for long-term PET. The ADCs reported here offer a quantitative basis for assessing the dosimetric safety of 118 Te radiopharmaceuticals.
