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Nanoliposomes Co-Encapsulating CT Imaging Contrast Agent and Photosensitizer for Enhanced, Imaging Guided Photodynamic Therapy of Cancer.

ABSTRACT: Fluorescence (FL) and X-ray computed tomography (CT) imaging-guided photodynamic therapy (PDT) can provide a powerful theranostic tool to visualize, monitor, and treat cancer and other diseases with enhanced accuracy and efficacy. Methods: In this study, clinically approved iodinated CT imaging contrast agent (CTIA) iodixanol and commercially available photosensitizer (PS) meso-tetrakis (4-sulphonatophenyl) porphine (TPPS₄) were co-encapsulated in biocompatible PEGylated nanoliposomes (NL) for enhanced anticancer PDT guided by bimodal (FL and CT) imaging. Results: The NL co-encapsulation of iodixanol and TPPS₄ (LIT) lead to an increase in singlet oxygen generation by PS via the intraparticle heavy-atom (iodine) effect on PS molecules, as it was confirmed by both direct and indirect measurements of singlet oxygen production. The confocal imaging and PDT of cancer cells were performed in vitro, exhibiting the cellular uptake of TPPS₄ formulations and enhanced PDT efficacy of LIT. Meanwhile, bimodal (FL and CT) imaging was also conducted with tumor-bearing mice and the imaging results manifested high-efficient accumulation and retention of LIT in tumors. Moreover, PDT of tumor in vivo was shown to be drastically more efficient with LIT than with other formulations of TPPS₄. Conclusion: This study demonstrated that LIT can serve as a highly efficient theranostic nanoplatform for enhanced anticancer PDT guided by bimodal (FL and CT) imaging.

SUBMITTER: Xu H

PROVIDER: S-EPMC6401496 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Project description:BackgroundSolitary pulmonary nodules (SPNs) measuring 8 to 30 mm in diameter require further workup to determine the likelihood of malignancy.Research questionWhat is the diagnostic performance of a lung cancer prediction convolutional neural network (LCP-CNN) in SPNs using unenhanced and contrast-enhanced CT imaging compared with the current clinical workup?Study design and methodsThis was a post hoc analysis of the Single Pulmonary Nodule Investigation: Accuracy and Cost-Effectiveness of Dynamic Contrast Enhanced Computed Tomography in the Characterisation of Solitary Pulmonary Nodules trial, a prospective multicenter study comparing the diagnostic accuracy of dynamic contrast-enhanced (DCE) CT imaging with PET imaging in SPNs. The LCP-CNN was designed and validated in an external cohort. LCP-CNN-generated risk scores were created from the noncontrast and contrast-enhanced CT scan images from the DCE CT imaging. The gold standard was histologic analysis or 2 years of follow-up. The area under the receiver operating characteristic curves (AUC) were calculated using LCP-CNN score, maximum standardized uptake value, and DCE CT scan maximum enhancement and were compared using the DeLong test.ResultsTwo hundred seventy participants (mean ± SD age, 68.3 ± 8.8 years; 49% women) underwent PET with CT scan imaging and DCE CT imaging with CT scan data available centrally for LCP-CNN analysis. The accuracy of the LCP-CNN on the noncontrast images (AUC, 0.83; 95% CI, 0.79-0.88) was superior to that of DCE CT imaging (AUC, 0.76; 95% CI, 0.69-0.82; P = .03) and equal to that of PET with CT scan imaging (AUC, 0.86; 95% CI, 0.81-0.90; P = .35). The presence of contrast resulted in a small reduction in diagnostic accuracy, with the AUC falling from 0.83 (95% CI, 0.79-0.88) on the noncontrast images to 0.80 to 0.83 after contrast (P < .05 for 240 s after contrast only).InterpretationAn LCP-CNN algorithm provides an AUC equivalent to PET with CT scan imaging in the diagnosis of solitary pulmonary nodules.Trial registrationClinicalTrials.gov Identifier; No.: NCT02013063.

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Nanoliposomes Co-Encapsulating CT Imaging Contrast Agent and Photosensitizer for Enhanced, Imaging Guided Photodynamic Therapy of Cancer.

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