Dataset Information

Analysis of PET parameters predicting response to radiotherapy for myeloid sarcoma.

ABSTRACT:

Purpose

Positron-emission tomography (PET)-CT has recently been used for diagnostic imaging and radiotherapy for myeloid sarcoma, but there is little research on predicting the response of radiotherapy. The aim of this study was to analyze the association between PET-CT variables and the response to radiotherapy in patients with myeloid sarcoma.

Materials and methods

This study was conducted in myeloid sarcoma patients who received radiotherapy and PET-CT before and after radiotherapy. The response to radiotherapy was evaluated based on the European Organization for Research and Treatment of Cancer PET response criteria, and binary regression analysis was performed to assess the factors predicting reductions in the maximum standardized uptake value (SUVmax).

Results

Twenty-seven sites in 12 patients were included in the study. Complete metabolic responses were seen in 24 patients after radiotherapy, a partial metabolic response in one, and progressive metabolic disease in two patients. The prescribed dose of more than 3000 cGy10 was significantly greater in the treatment control group (P = 0.024). In binary logistic regression analysis predicting reductions in the SUVmax of more than 70% after radiotherapy, the pretreatment SUVmax (≥ 7.5) and further chemotherapy after radiotherapy showed significant differences in univariate and multivariate analyses.

Conclusion

Good metabolic responses (complete or partial) to radiotherapy were achieved in 92.6% of the myeloid sarcoma patients. Radiation doses < 3000 cGy10 and increased SUVmax were related to treatment failure and high SUVmax before radiotherapy was a factor influencing SUVmax reduction. Further large-scale studies are needed.

SUBMITTER: Choi KH

PROVIDER: S-EPMC8687562 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Analysis of PET parameters predicting response to radiotherapy for myeloid sarcoma.

Choi Kyu Hye KH Song Jin Ho JH Kwak Yoo-Kang YK Lee Jong Hoon JH Jang Hong Seok HS

PloS one 20211220 12

<h4>Purpose</h4>Positron-emission tomography (PET)-CT has recently been used for diagnostic imaging and radiotherapy for myeloid sarcoma, but there is little research on predicting the response of radiotherapy. The aim of this study was to analyze the association between PET-CT variables and the response to radiotherapy in patients with myeloid sarcoma.<h4>Materials and methods</h4>This study was conducted in myeloid sarcoma patients who received radiotherapy and PET-CT before and after radiothe ...[more]

PMID: 34929016

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Project description:PurposeIn positron emission tomography quantification, multiple pharmacokinetic parameters are typically estimated from each time activity curve. Conventionally all but the parameter of interest are discarded before performing subsequent statistical analysis. However, we assert that these discarded parameters also contain relevant information which can be exploited to improve the precision and power of statistical analyses on the parameter of interest. Properly taking this into account can thereby draw more informative conclusions without collecting more data.MethodsBy applying a hierarchical multifactor multivariate Bayesian approach, all estimated parameters from all regions can be analysed at once. We refer to this method as Parameters undergoing Multivariate Bayesian Analysis (PuMBA). We simulated patient-control studies with different radioligands, varying sample sizes and measurement error to explore its performance, comparing the precision, statistical power, false positive rate and bias of estimated group differences relative to univariate analysis methods.ResultsWe show that PuMBA improves the statistical power for all examined applications relative to univariate methods without increasing the false positive rate. PuMBA improves the precision of effect size estimation, and reduces the variation of these estimates between simulated samples. Furthermore, we show that PuMBA yields performance improvements even in the presence of substantial measurement error. Remarkably, owing to its ability to leverage information shared between pharmacokinetic parameters, PuMBA even shows greater power than conventional univariate analysis of the true binding values from which the parameters were simulated. Across all applications, PuMBA exhibited a small degree of bias in the estimated outcomes; however, this was small relative to the variation in estimated outcomes between simulated datasets.ConclusionPuMBA improves the precision and power of statistical analysis of PET data without requiring the collection of additional measurements. This makes it possible to study new research questions in both new and previously collected data. PuMBA therefore holds great promise for the field of PET imaging.

Dataset Information

Analysis of PET parameters predicting response to radiotherapy for myeloid sarcoma.

Purpose

Materials and methods

Results

Conclusion

Publications

Analysis of PET parameters predicting response to radiotherapy for myeloid sarcoma.

Similar Datasets

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