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Purpose: To evaluate the outcomes of resin-based yttrium-90 ( 90 Y) transarterial radioembolization (TARE) for hepatocellular carcinoma (HCC) as a bridging or downstaging therapy to liver transplantation (LT) in terms of safety, tumor response, recurrence, and survival., Materials and Methods: A single-center retrospective analysis of patients with HCC treated with resin-based TARE as bridging or downstaging treatment to LT between January 2006 and April 2021 was performed. TARE-related liver toxicity was assessed. Imaging data were analyzed to assess tumor response. Histopathological analysis of explant livers was performed to assess HCC necrosis. Survival and bridging/downstaging success predictor analysis was performed., Results: Thirty-six patients underwent resin-based TARE with the intention to bridge (33%) or downstage (67%) to LT. Overall, 44% had ≥3 HCC lesions, and 53% had bilobar disease. Median largest tumor diameter was 3.4 cm. TARE was segmental, lobar, and bilobar in 20%, 36%, and 44% of cases, respectively. In total, 17% had Grade 3 bilirubin toxicities. The objective response rate per modified Response Evaluation Criteria in Solid Tumours was 72%. Patients meeting the United Network for Organ Sharing Downstaging criteria had higher chances of successful bridging/downstaging. Twenty-three patients were transplanted. Complete pathological response was noted in 30% of explant livers. Posttransplant tumor recurrence occurred in 26% within a median follow-up period of 1,710 days. Estimated 5-year progression-free, disease-specific, and overall survival rates after LT were 89%, 69%, and 89%, respectively. For the entire patient cohort, these survival rates were 87%, 53%, and 70%, respectively., Conclusions: Resin-based 90 Y TARE can be considered a valuable treatment option for bridging or downstaging patients with HCC to LT, including patients requiring lobar or bilobar TARE for extensive tumoral disease., (Copyright © 2024 SIR. Published by Elsevier Inc. All rights reserved.)

Background: Selective internal radiation therapy (SIRT) is a promising treatment for unresectable hepatic malignancies. Predictive dose calculation based on a simulation using 99m Tc-labeled macro-aggregated albumin ( 99m Tc-MAA) before the treatment is considered as a potential tool for patient-specific treatment planning. Post-treatment dose measurement is mainly performed to confirm the planned absorbed dose to the tumor and non-tumor liver volumes. This study compared the predicted and measured absorbed dose distributions., Methods: Thirty-one patients (67 tumors) treated by SIRT with resin microspheres were analyzed. Predicted and delivered absorbed dose was calculated using 99m Tc-MAA-SPECT and 90 Y-TOF-PET imaging. The voxel-level dose distribution was derived using the local deposition model. Liver perfusion territories and tumors have been delineated on contrast-enhanced CBCT images, which have been acquired during the 99m Tc-MAA work-up. Several dose-volume histogram (DVH) parameters together with the mean dose for liver perfusion territories and non-tumoral and tumoral compartments were evaluated., Results: A strong correlation between the predicted and measured mean dose for non-tumoral volume was observed (r = 0.937). The ratio of measured and predicted mean dose to this volume has a first, second, and third interquartile range of 0.83, 1.05, and 1.25. The difference between the measured and predicted mean dose did not exceed 11 Gy. The correlation between predicted and measured mean dose to the tumor was moderate (r = 0.623) with a mean difference of - 9.3 Gy. The ratio of measured and predicted tumor mean dose had a median of 1.01 with the first and third interquartile ranges of 0.58 and 1.59, respectively. Our results suggest that 99m Tc-MAA-based dosimetry could predict under or over dosing of the non-tumoral liver parenchyma for almost all cases. For more than two thirds of the tumors, a predictive absorbed dose correctly indicated either good tumor dose coverage or under-dosing of the tumor., Conclusion: Our results highlight the predictive value of 99m Tc-MAA-based dose estimation to predict non-tumor liver irradiation, which can be applied to prescribe an optimized activity aiming at avoiding liver toxicity. Compared to non-tumoral tissue, a poorer agreement between predicted and measured absorbed dose is observed for tumors.

A capillary electrophoresis method with capacitively coupled contactless conductivity detection (CE-C(4)D) has been developed, optimized and validated for the determination of ciprofloxacin. Ciprofloxacin is a member of the fluoroquinolone antibiotics with a broad spectrum bactericidal activity and recommended for complicated respiratory infections, sexually transmitted diseases, tuberculosis, bacterial diarrhea etc. Method development was conducted with major focus on the quality by design (QbD) approach. During method development, multiple buffers were tried at different ionic strength. However, the optimized method finally involved a very simple background electrolyte, monosodium citrate at a concentration of 10mM without pH adjustment. The optimized CE-C(4)D method involved an uncoated fused silica capillary (59/39cm, 50μm i.d.) and hydrodynamic sample injection at a pressure of 0.5 p.s.i. for 5s. The actual separation was conducted for 10min at normal polarity with a voltage of 20kV corresponding to 5.9μA current. LiCl (1mg/mL) was used as an internal standard. The optimized method is robust and accurate (recovery >98%) which rendered the ciprofloxacin peak within five minutes with good linearity (R(2)>0.999) in the concentration range of 0.0126-0.8mg/mL. The repeatability is expressed by percentage relative standard deviation (%RSD) of the relative peak areas (RPA) and it showed good repeatability both intra-day (<3%) and inter-day (3.1%). This method, proven to be free of matrix interference, showed that the estimated percent content of ciprofloxacin (102%) was within the official requirements. Moreover, due to its ease of use and robustness, the method should also be applicable in less well controlled laboratory environments., (Copyright © 2016 Elsevier B.V. All rights reserved.)