Objectives: Absorbed dose to red marrow (D) can be calculated using blood dosimetry. However, this method is laborious and invasive. Therefore, image-based dosimetry is the method of choice. Nonetheless, the commercial software is expensive. The goal of this work was to develop a simplified excel spreadsheet for image-based radioiodine red marrow dosimetry.
Methods: The serial whole-body images (acquired at 2, 6, 24, 48, and 72 hours) of 29 patients from the routine pretherapeutic dosimetry protocol were retrospectively reanalyzed. The commercial OLINDA/EXM image-based dosimetry software was used to calculate the whole-body time-integrated activity coefficient (TIAC) and D [in terms of absorbed dose coefficient (d)]. For the simplified excel spreadsheet, the wholebody count was obtained from the vendor-supplied software. Then, the TIAC was computed by a fitting time-activity curve using an Excel function. S factor was taken from other publications and scaled according to the patient-specific mass. A comparison of the TIAC and d from both methods was done using a non-inferiority test using a paired t-test or the Wilcoxon signed-rank test.
Results: The TIAC showed no significant difference between both methods (p=0.243). The calculated D from a simplified Excel spreadsheet was assumed to be statistically non-inferior to the commercial OLINDA/EXM image-based dosimetry software with the non-inferiority margin of 0.02 (p<0.05).
Conclusion: The dose assessment from a simplified Excel spreadsheet is feasible and relatively low cost compared to the commercial OLINDA/EXM image-based dosimetry software.
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http://dx.doi.org/10.4274/mirt.galenos.2020.71473 | DOI Listing |
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Stein Eye Institute, Department of Ophthalmology, David Geffen School of Medicine, Los Angeles, CA, United States.
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December 2024
Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, MI, 48109, USA.
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View Article and Find Full Text PDFSci Rep
December 2024
Computer Science Department, Ruhr West University of Applied Sciences, Bottrop, Germany.
Selecting pretrained models for image classification often involves computationally intensive finetuning. This study addresses a research gap in the standardized evaluation of transferability scores, which could simplify model selection by ranking pretrained models without exhaustive finetuning. The motivation is to reduce the computational burden of model selection through a consistent approach that guides practitioners in balancing accuracy and efficiency across tasks.
View Article and Find Full Text PDFQ J Exp Psychol (Hove)
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Department of Experimental Psychology, Ghent University, Gent, Belgium.
This study investigates whether estimates of familiarity, valence, arousal, and concreteness based on artificial intelligence (AI) are useful alternatives to word counts and human ratings in Spanish. We replicate and extend previous findings in English and show that GPT-4o is effective in estimating these word features. Validity checks even suggest that AI-generated estimates sometimes outperform traditional measurements.
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