Magnetic resonance in medicine · 2026
Optimization of Diffusion MRI With Consideration of the Signal Decay in Biological Tissues.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Kuczera Stefan, Maier Stephan E
Аннотация
PURPOSE: Devising methodology to characterize and optimize acquisition schemes for biological tissues, such as the prostate, that produce model-based synthetic diffusion-weighted images and derived model parameters with predictable SNR improvement.
METHODS: The averaging effect (AE) in synthetic diffusion-weighted images obtained through fitting of various signal decay models to signals measured over 21 linearly spaced b-values between 0 and 2000 s / mm 2 $$ 2000\mathrm{s}/{\mathrm{mm}}^2 $$ is determined with analytic expressions. Similarly, the standard deviation of a retrospective 2-point ADC fit based on the synthetic data is analyzed. Furthermore, acquisition schemes that achieve constant SNR or constant AE for synthetic images over the same b-value range are devised by means of numerical optimization using either a custom iterative method or a standard function optimizer. These acquisition schemes are verified by measurements on a phantom with a non-monoexponential diffusion signal decay combined with a bootstrapping approach to increase the number of data samples.
RESULTS: The dependence of AE on model function and parameters is complex. Repeated measurements at specific b-values can boost AE locally, while improvements in ADC uncertainty are particularly pronounced for repetitions of the higher b-value. Optimization of acquisition schemes generally results in discrete b-values, whereby the number of b-values corresponds to the number of model parameters. Results from phantom measurements are in agreement with the theoretical predictions.
CONCLUSION: The presented analytical calculations and numerical optimizations can be useful to improve acquisition schemes under various experimental conditions and clinical needs.
METHODS: The averaging effect (AE) in synthetic diffusion-weighted images obtained through fitting of various signal decay models to signals measured over 21 linearly spaced b-values between 0 and 2000 s / mm 2 $$ 2000\mathrm{s}/{\mathrm{mm}}^2 $$ is determined with analytic expressions. Similarly, the standard deviation of a retrospective 2-point ADC fit based on the synthetic data is analyzed. Furthermore, acquisition schemes that achieve constant SNR or constant AE for synthetic images over the same b-value range are devised by means of numerical optimization using either a custom iterative method or a standard function optimizer. These acquisition schemes are verified by measurements on a phantom with a non-monoexponential diffusion signal decay combined with a bootstrapping approach to increase the number of data samples.
RESULTS: The dependence of AE on model function and parameters is complex. Repeated measurements at specific b-values can boost AE locally, while improvements in ADC uncertainty are particularly pronounced for repetitions of the higher b-value. Optimization of acquisition schemes generally results in discrete b-values, whereby the number of b-values corresponds to the number of model parameters. Results from phantom measurements are in agreement with the theoretical predictions.
CONCLUSION: The presented analytical calculations and numerical optimizations can be useful to improve acquisition schemes under various experimental conditions and clinical needs.