Development of a calibration protocol for quantitative imaging for molecular radiotherapy dosimetry

2017 ◽  
Vol 140 ◽  
pp. 355-360 ◽  
Author(s):  
J. Wevrett ◽  
A. Fenwick ◽  
J. Scuffham ◽  
A. Nisbet
Keyword(s):  
Quantitative Imaging ◽  
Molecular Radiotherapy ◽  
Calibration Protocol ◽  
Radiotherapy Dosimetry

scholarly journals Improving molecular radiotherapy dosimetry using anthropomorphic calibration

2019 ◽  
Vol 58 ◽  
pp. 40-46 ◽  
Author(s):  
Emlyn Price ◽  
Andrew P. Robinson ◽  
David M. Cullen ◽  
Jill Tipping ◽  
Nick Calvert ◽  
...  
Keyword(s):  
Molecular Radiotherapy ◽  
Radiotherapy Dosimetry

scholarly journals A multicentre and multi-national evaluation of the accuracy of quantitative Lu-177 SPECT/CT imaging performed within the MRTDosimetry project

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Johannes Tran-Gia ◽  
Ana M. Denis-Bacelar ◽  
Kelley M. Ferreira ◽  
Andrew P. Robinson ◽  
Nicholas Calvert ◽  
...  
Keyword(s):  
Quantitative Imaging ◽  
Ct Imaging ◽  
Partial Volume Correction ◽  
Partial Volume ◽  
Volume Correction ◽  
Activity Recovery ◽  
Calibration Protocol ◽  
Imaging Performance ◽  
Comparison Exercise

Abstract Purpose Patient-specific dosimetry is required to ensure the safety of molecular radiotherapy and to predict response. Dosimetry involves several steps, the first of which is the determination of the activity of the radiopharmaceutical taken up by an organ/lesion over time. As uncertainties propagate along each of the subsequent steps (integration of the time–activity curve, absorbed dose calculation), establishing a reliable activity quantification is essential. The MRTDosimetry project was a European initiative to bring together expertise in metrology and nuclear medicine research, with one main goal of standardizing quantitative 177Lu SPECT/CT imaging based on a calibration protocol developed and tested in a multicentre inter-comparison. This study presents the setup and results of this comparison exercise. Methods The inter-comparison included nine SPECT/CT systems. Each site performed a set of three measurements with the same setup (system, acquisition and reconstruction): (1) Determination of an image calibration for conversion from counts to activity concentration (large cylinder phantom), (2) determination of recovery coefficients for partial volume correction (IEC NEMA PET body phantom with sphere inserts), (3) validation of the established quantitative imaging setup using a 3D printed two-organ phantom (ICRP110-based kidney and spleen). In contrast to previous efforts, traceability of the activity measurement was required for each participant, and all participants were asked to calculate uncertainties for their SPECT-based activities. Results Similar combinations of imaging system and reconstruction lead to similar image calibration factors. The activity ratio results of the anthropomorphic phantom validation demonstrate significant harmonization of quantitative imaging performance between the sites with all sites falling within one standard deviation of the mean values for all inserts. Activity recovery was underestimated for total kidney, spleen, and kidney cortex, while it was overestimated for the medulla. Conclusion This international comparison exercise demonstrates that harmonization of quantitative SPECT/CT is feasible when following very specific instructions of a dedicated calibration protocol, as developed within the MRTDosimetry project. While quantitative imaging performance demonstrates significant harmonization, an over- and underestimation of the activity recovery highlights the limitations of any partial volume correction in the presence of spill-in and spill-out between two adjacent volumes of interests.

Fluorescent potentiometric dyes for membrane-potential imaging

1994 ◽  
Vol 52 ◽  
pp. 166-167
Author(s):  
Leslie M. Loew
Keyword(s):  
Membrane Potential ◽  
Single Cells ◽  
Quantitative Imaging ◽  
Optical Recording ◽  
Biological Processes ◽  
Major Focus ◽  
The Past ◽  
Excitable Systems ◽  
Major Application ◽  
The Impact

A major application of potentiometric dyes has been the multisite optical recording of electrical activity in excitable systems. After being championed by L.B. Cohen and his colleagues for the past 20 years, the impact of this technology is rapidly being felt and is spreading to an increasing number of neuroscience laboratories. A second class of experiments involves using dyes to image membrane potential distributions in single cells by digital imaging microscopy - a major focus of this lab. These studies usually do not require the temporal resolution of multisite optical recording, being primarily focussed on slow cell biological processes, and therefore can achieve much higher spatial resolution. We have developed 2 methods for quantitative imaging of membrane potential. One method uses dual wavelength imaging of membrane-staining dyes and the other uses quantitative 3D imaging of a fluorescent lipophilic cation; the dyes used in each case were synthesized for this purpose in this laboratory.

Do we need Quantitative Imaging?

2020 ◽  
Vol 59 (03) ◽  
pp. 225-226 ◽  
Author(s):  
Janet F. Eary ◽  
Winfried Brenner
Keyword(s):  
Quantitative Imaging

The Software «MMI–calibration 3.0»

Metrologiya ◽  
2020 ◽  
pp. 16-24
Author(s):  
Alexandr D. Chikmarev
Keyword(s):  
Power Series ◽  
Data Processing ◽  
Statistical Treatment ◽  
Correction Function ◽  
Calibration Function ◽  
Measuring Instrument ◽  
Working Standard ◽  
Calibration Protocol ◽  
Error Probabilities ◽  
Continuous Power

A single program has been developed to ensure that the final result of the data processing of the measurement calibration protocol is obtained under normal conditions. The calibration result contains a calibration function or a correction function in the form of a continuous sedate series and a calibration chart based on typical additive error probabilities. Solved the problem of the statistical treatment of the calibration protocol measuring in normal conditions within a single program “MMI–calibration 3.0” that includes identification of the calibration function in a continuous power series of indications of a measuring instrument and chart calibration. An example of solving the problem of calibration of the thermometer by the working standard of the 3rd grade with the help of the “MMI-calibration 3.0” program.

Semiconductor Quantum Dots for Multicolor Fluorescence Imaging and Spectroscopy of Single Cancer Cells

2003 ◽  
Vol 773 ◽  
Author(s):  
Xiaohu Gao ◽  
Shuming Nie ◽  
Wallace H. Coulter
Keyword(s):  
Quantum Dots ◽  
Cancer Cells ◽  
Fluorescence Imaging ◽  
Organic Dyes ◽  
Fluorescent Proteins ◽  
Single Cells ◽  
Quantitative Imaging ◽  
Semiconductor Quantum Dots ◽  
Single Cancer ◽  
Imaging And Spectroscopy

AbstractLuminescent quantum dots (QDs) are emerging as a new class of biological labels with unique properties and applications that are not available from traditional organic dyes and fluorescent proteins. Here we report new developments in using semiconductor quantum dots for quantitative imaging and spectroscopy of single cancer cells. We show that both live and fixed cells can be labeled with multicolor QDs, and that single cells can be analyzed by fluorescence imaging and wavelength-resolved spectroscopy. These results raise new possibilities in cancer imaging, molecular profiling, and disease staging.

scholarly journals Incorporating radiomics into clinical trials: expert consensus on considerations for data-driven compared to biologically driven quantitative biomarkers

2021 ◽  
Author(s):  
Laure Fournier ◽  
Lena Costaridou ◽  
Luc Bidaut ◽  
Nicolas Michoux ◽  
Frederic E. Lecouvet ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Quantitative Imaging ◽  
A Priori ◽  
External Validation ◽  
Data Driven ◽  
Imaging Biomarkers ◽  
Clinical Validation ◽  
Biological Processes ◽  
Imaging Data ◽  
Selection Of

Abstract Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. Key Points • Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the dataset compared to sample size, making adequate diversity of the data, cross-validation and external validation essential to mitigate the risks of spurious associations and overfitting. • Use of radiomic signatures within clinical trials requires multistep standardisation of image acquisition, image analysis and data mining processes. • Biological correlation may be established after clinical validation but is not mandatory.

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