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High-throughput high-volume nuclear imaging for preclinical in vivo compound screening §

View Article: PubMed Central - PubMed

ABSTRACT

Background: Preclinical single-photon emission computed tomography (SPECT)/CT imaging studies are hampered by low throughput, hence are found typically within small volume feasibility studies. Here, imaging and image analysis procedures are presented that allow profiling of a large volume of radiolabelled compounds within a reasonably short total study time. Particular emphasis was put on quality control (QC) and on fast and unbiased image analysis.

Methods: 2–3 His-tagged proteins were simultaneously radiolabelled by 99mTc-tricarbonyl methodology and injected intravenously (20 nmol/kg; 100 MBq; n = 3) into patient-derived xenograft (PDX) mouse models. Whole-body SPECT/CT images of 3 mice simultaneously were acquired 1, 4, and 24 h post-injection, extended to 48 h and/or by 0–2 h dynamic SPECT for pre-selected compounds. Organ uptake was quantified by automated multi-atlas and manual segmentations. Data were plotted automatically, quality controlled and stored on a collaborative image management platform. Ex vivo uptake data were collected semi-automatically and analysis performed as for imaging data.

Results: >500 single animal SPECT images were acquired for 25 proteins over 5 weeks, eventually generating >3500 ROI and >1000 items of tissue data. SPECT/CT images clearly visualized uptake in tumour and other tissues even at 48 h post-injection. Intersubject uptake variability was typically 13% (coefficient of variation, COV). Imaging results correlated well with ex vivo data.

Conclusions: The large data set of tumour, background and systemic uptake/clearance data from 75 mice for 25 compounds allows identification of compounds of interest. The number of animals required was reduced considerably by longitudinal imaging compared to dissection experiments. All experimental work and analyses were accomplished within 3 months expected to be compatible with drug development programmes. QC along all workflow steps, blinding of the imaging contract research organization to compound properties and automation provide confidence in the data set. Additional ex vivo data were useful as a control but could be omitted from future studies in the same centre. For even larger compound libraries, radiolabelling could be expedited and the number of imaging time points adapted to increase weekly throughput. Multi-atlas segmentation could be expanded via SPECT/MRI; however, this would require an MRI-compatible mouse hotel. Finally, analysis of nuclear images of radiopharmaceuticals in clinical trials may benefit from the automated analysis procedures developed.

Electronic supplementary material: The online version of this article (doi:10.1186/s13550-017-0281-4) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus

Exemplary plots of imaging data (top row, mean and SEM error bars for N = 3) and ex vivo data (bottom row, individual data points). a % ID/mL in left kidney ROIs (all compounds, all time points). b % ID/mL data of compound 17 (all ROIs, all time points). c % ID/g in liver in all animals (≈24 or 48 h pi). d % ID/g in tumour in all animals (≈24 or 48 h pi)
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Fig3: Exemplary plots of imaging data (top row, mean and SEM error bars for N = 3) and ex vivo data (bottom row, individual data points). a % ID/mL in left kidney ROIs (all compounds, all time points). b % ID/mL data of compound 17 (all ROIs, all time points). c % ID/g in liver in all animals (≈24 or 48 h pi). d % ID/g in tumour in all animals (≈24 or 48 h pi)

Mentions: Image analysis produced SPECT data of ≈4000 ROIs. Examples for SPECT data plots are provided in Fig. 3a, b. While each plot condenses information from at least 9 SPECT images (three animals, three time points) or even from ≈500 (all animals, all time points as in Fig. 3a), the subdivision into tissues and compounds, and the choice of parameters and various plot types resulted again in an expansion, here to >1000 plots. This was managed by tables of contents in PDF slide decks with a hierarchical folder-structure allowing quick access to any plot of interest.Fig. 3


High-throughput high-volume nuclear imaging for preclinical in vivo compound screening §
Exemplary plots of imaging data (top row, mean and SEM error bars for N = 3) and ex vivo data (bottom row, individual data points). a % ID/mL in left kidney ROIs (all compounds, all time points). b % ID/mL data of compound 17 (all ROIs, all time points). c % ID/g in liver in all animals (≈24 or 48 h pi). d % ID/g in tumour in all animals (≈24 or 48 h pi)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5383912&req=5

Fig3: Exemplary plots of imaging data (top row, mean and SEM error bars for N = 3) and ex vivo data (bottom row, individual data points). a % ID/mL in left kidney ROIs (all compounds, all time points). b % ID/mL data of compound 17 (all ROIs, all time points). c % ID/g in liver in all animals (≈24 or 48 h pi). d % ID/g in tumour in all animals (≈24 or 48 h pi)
Mentions: Image analysis produced SPECT data of ≈4000 ROIs. Examples for SPECT data plots are provided in Fig. 3a, b. While each plot condenses information from at least 9 SPECT images (three animals, three time points) or even from ≈500 (all animals, all time points as in Fig. 3a), the subdivision into tissues and compounds, and the choice of parameters and various plot types resulted again in an expansion, here to >1000 plots. This was managed by tables of contents in PDF slide decks with a hierarchical folder-structure allowing quick access to any plot of interest.Fig. 3

View Article: PubMed Central - PubMed

ABSTRACT

Background: Preclinical single-photon emission computed tomography (SPECT)/CT imaging studies are hampered by low throughput, hence are found typically within small volume feasibility studies. Here, imaging and image analysis procedures are presented that allow profiling of a large volume of radiolabelled compounds within a reasonably short total study time. Particular emphasis was put on quality control (QC) and on fast and unbiased image analysis.

Methods: 2–3 His-tagged proteins were simultaneously radiolabelled by 99mTc-tricarbonyl methodology and injected intravenously (20 nmol/kg; 100 MBq; n = 3) into patient-derived xenograft (PDX) mouse models. Whole-body SPECT/CT images of 3 mice simultaneously were acquired 1, 4, and 24 h post-injection, extended to 48 h and/or by 0–2 h dynamic SPECT for pre-selected compounds. Organ uptake was quantified by automated multi-atlas and manual segmentations. Data were plotted automatically, quality controlled and stored on a collaborative image management platform. Ex vivo uptake data were collected semi-automatically and analysis performed as for imaging data.

Results: >500 single animal SPECT images were acquired for 25 proteins over 5 weeks, eventually generating >3500 ROI and >1000 items of tissue data. SPECT/CT images clearly visualized uptake in tumour and other tissues even at 48 h post-injection. Intersubject uptake variability was typically 13% (coefficient of variation, COV). Imaging results correlated well with ex vivo data.

Conclusions: The large data set of tumour, background and systemic uptake/clearance data from 75 mice for 25 compounds allows identification of compounds of interest. The number of animals required was reduced considerably by longitudinal imaging compared to dissection experiments. All experimental work and analyses were accomplished within 3 months expected to be compatible with drug development programmes. QC along all workflow steps, blinding of the imaging contract research organization to compound properties and automation provide confidence in the data set. Additional ex vivo data were useful as a control but could be omitted from future studies in the same centre. For even larger compound libraries, radiolabelling could be expedited and the number of imaging time points adapted to increase weekly throughput. Multi-atlas segmentation could be expanded via SPECT/MRI; however, this would require an MRI-compatible mouse hotel. Finally, analysis of nuclear images of radiopharmaceuticals in clinical trials may benefit from the automated analysis procedures developed.

Electronic supplementary material: The online version of this article (doi:10.1186/s13550-017-0281-4) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus