Dataset Information

Precision Nanomedicine Using Dual PET and MR Temperature Imaging-Guided Photothermal Therapy.

ABSTRACT: Imaging-based techniques have enabled the direct integration of noninvasive imaging with minimally invasive interventions such as photothermal therapy (PTT) to improve the precision of treatment.

Methods

We investigated the feasibility of PTT for ovarian cancer under the guidance of PET and MR temperature imaging using copper sulfide nanoparticles (CuS NPs). The tumor distribution of the CuS NPs after systemic administration was assessed using highly sensitive, quantifiable PET imaging. Two wavelengths of near-infrared (NIR) lasers-808 and 980 nm-were tested for PTT using noninvasive MR temperature imaging real-time monitoring.

Results

The in vivo studies revealed that the 980-nm NIR laser had better photothermal effects than the 808-nm NIR laser. These results were in accord with the histologic findings. In vivo PTT using CuS NPs combined with 980-nm laser irradiation achieved significant tumor ablation compared with no treatment control in both subcutaneous (P = 0.007) and orthotopic (P < 0.001) models of ovarian cancer with regard to the percentage of necrotic damage.

Conclusion

Our results indicate that real-time monitoring of the accuracy of PTT is a promising approach for future clinical translation of this emerging thermal ablation technique.

SUBMITTER: Zhou M

PROVIDER: S-EPMC5093070 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Publications

Precision Nanomedicine Using Dual PET and MR Temperature Imaging-Guided Photothermal Therapy.

Zhou Min M Melancon Marites M Stafford R Jason RJ Li Junjie J Nick Alpa M AM Tian Mei M Sood Anil K AK Li Chun C

Journal of nuclear medicine : official publication, Society of Nuclear Medicine 20160609 11

Imaging-based techniques have enabled the direct integration of noninvasive imaging with minimally invasive interventions such as photothermal therapy (PTT) to improve the precision of treatment.<h4>Methods</h4>We investigated the feasibility of PTT for ovarian cancer under the guidance of PET and MR temperature imaging using copper sulfide nanoparticles (CuS NPs). The tumor distribution of the CuS NPs after systemic administration was assessed using highly sensitive, quantifiable PET imaging. T ...[more]

PMID: 27283932

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Project description:Accurate regional brain quantitative PET measurements, particularly when using partial volume correction, rely on robust image registration between PET and MR images. We argue here that the precision, and hence the uncertainty, of MR-PET image registration is mainly driven by the registration implementation and the quality of PET images due to their lower resolution and higher noise compared to the structural MR images. We propose a dedicated uncertainty analysis for quantifying the precision of MR-PET registration, centred around the bootstrap resampling of PET list-mode events to generate multiple PET image realisations with different noise (count) levels. The effects of PET image reconstruction parameters, such as the use of attenuation and scatter corrections and different number of iterations, on the precision and accuracy of MR-PET registration were investigated. In addition, the performance of four software packages with their default settings for rigid inter-modality image registration were considered: NiftyReg, Vinci, FSL and SPM. Four distinct PET image distributions made of two early time frames (similar to cortical FDG) and two late frames using two amyloid PET dynamic acquisitions of one amyloid positive and one amyloid negative participants were investigated. For the investigated four PET frames, the biggest impact on the uncertainty was observed between registration software packages (up to 10-fold difference in precision) followed by the reconstruction parameters. On average, the lowest uncertainty for different PET frames and brain regions was observed with SPM and two iterations of fully quantitative image reconstruction. The observed uncertainty for the varying PET count-level (from 5% to 60%) was slightly lower than for the reconstruction parameters. We also observed that the registration uncertainty in quantitative PET analysis depends on amyloid status of the considered PET frames, with increased uncertainty (up to three times) when using post-reconstruction partial volume correction. This analysis is applicable for PET data obtained from either PET/MR or PET/CT scanners.

Dataset Information

Precision Nanomedicine Using Dual PET and MR Temperature Imaging-Guided Photothermal Therapy.

Methods

Results

Conclusion

Publications

Precision Nanomedicine Using Dual PET and MR Temperature Imaging-Guided Photothermal Therapy.

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