Thapa, Diwash

Abstract Background Dual‐contrast imaging of iodine and bismuth has shown promise in previous phantom and animal studies utilizing spectral CT. However, these studies often employed Pepto‐Bismol containing bismuth subsalicylate with dosages exceeding the recommended limits for human consumption, limiting their clinical applicability. Purpose The purpose of this study was to improve iodine–bismuth dual‐contrast imaging on a clinical photon‐counting CT (PCCT) system using a noise‐optimized virtual monoenergetic imaging (VMI) approach. Methods Four bismuth samples (0.6, 1.3, 2.5, and 5.1 mg/mL) and three iodine rods (1.0, 2.0, and 5.0 mg/mL) were inserted into a multi‐energy CT phantom and scanned on a PCCT system at 140 kV. VMIs were generated from 40 to 190 keV in 10 keV increments. Iodine and bismuth maps were computed for all possible keV pairs using a generic image‐based three‐material decomposition method and compared with maps generated from the original low‐/high‐energy PCCT images. Mass concentrations, noise levels, and individual as well as joint root‐mean‐square error (RMSE) for iodine and bismuth were measured to determine the optimal keV pair. The contrast‐to‐noise ratios (CNRs) of low concentration samples (bismuth: 0.6 and 1.3 mg/mL; iodine: 1.0 mg/mL) were calculated at the optimal keV pair and compared to the values determined with the original PCCT images. In an IRB‐approved feasibility study, a research patient was administered two doses of Pepto‐Bismol prior to a routine abdomen‐pelvis CT scan. Material decomposition was performed using both the original low‐/high‐energy images and the optimal VMI pair identified in the phantom study. Bismuth signals in the stomach and proximal small bowel were assessed qualitatively and quantitatively. Results The VMI pair of 110 and 190 keV was determined to be optimal, achieving the lowest joint RMSE of 0.49 mg/mL, compared to 1.42 mg/mL for the original low‐/high‐energy pair. It also yielded the highest CNR, representing a 190–318% improvement over the original low/high‐energy decomposition. Qualitatively, both phantom and patient studies demonstrated improved iodine–bismuth separation and reduced noise using the optimized VMI pair. Conclusions These findings suggest that noise‐optimized VMI selection can enhance dual‐contrast material decomposition performance on clinical PCCT, supporting its potential for translation into gastrointestinal imaging applications.

Background & Aims: Early-stage HCC can be treated with thermal ablation or stereotactic body radiation therapy (SBRT). We retrospectively compared local progression, mortality, and toxicity among patients with HCC treated with ablation or SBRT in a multicenter, US cohort. Approach & Results: We included adult patients with treatment-naïve HCC lesions without vascular invasion treated with thermal ablation or SBRT per individual physician or institutional preference from January 2012 to December 2018. Outcomes included local progression after a 3-month landmark period assessed at the lesion level and overall survival at the patient level. Inverse probability of treatment weighting was used to account for imbalances in treatment groups. The Cox proportional hazard modeling was used to compare progression and overall survival, and logistic regression was used for toxicity. There were 642 patients with 786 lesions (median size: 2.1 cm) treated with ablation or SBRT. In adjusted analyses, SBRT was associated with a reduced risk of local progression compared to ablation (aHR 0.30, 95% CI: 0.15–0.60). However, SBRT-treated patients had an increased risk of liver dysfunction at 3 months (absolute difference 5.5%, aOR 2.31, 95% CI: 1.13–4.73) and death (aHR 2.04, 95% CI: 1.44–2.88, p < 0.0001). Conclusions: In this multicenter study of patients with HCC, SBRT was associated with a lower risk of local progression compared to thermal ablation but higher all-cause mortality. Survival differences may be attributable to residual confounding, patient selection, or downstream treatments. These retrospective real-world data help guide treatment decisions while demonstrating the need for a prospective clinical trial.