Accuracy of respiratory motion measurement of 4D-MRI: A comparison between cine and sequential acquisition

Abstract

Purpose: The authors have recently developed a cine-mode T2*/T1-weighted 4D-MRI technique and a sequential-mode T2-weighted 4D-MRI technique for imaging respiratory motion. This study aims at investigating which 4D-MRI image acquisition mode, cine or sequential, provides more accurate measurement of organ motion during respiration. Methods: A 4D digital extended cardiac-torso (XCAT) human phantom with a hypothesized tumor was used to simulate the image acquisition and the 4D-MRI reconstruction. The respiratory motion was controlled by the given breathing signal profiles. The tumor was manipulated to move continuously with the surrounding tissue. The motion trajectories were measured from both sequential-and cine-mode 4D-MRI images. The measured trajectories were compared with the average trajectory calculated from the input profiles, which was used as references. The error in 4D-MRI tumor motion trajectory (E) was determined. In addition, the corresponding respiratory motion amplitudes of all the selected 2D images for 4D reconstruction were recorded. Each of the amplitude was compared with the amplitude of its associated bin on the average breathing curve. The mean differences from the average breathing curve across all slice positions (D) were calculated. A total of 500 simulated respiratory profiles with a wide range of irregularity (Ir) were used to investigate the relationship between D and Ir. Furthermore, statistical analysis of E and D using XCAT controlled by 20 cancer patients' breathing profiles was conducted. Wilcoxon Signed Rank test was conducted to compare two modes. Results: D increased faster for cine-mode (D = 1.17 × Ir + 0.23) than sequential-mode (D = 0.47 × Ir + 0.23) as irregularity increased. For the XCAT study using 20 cancer patients' breathing profiles, the median E values were significantly different: 0.12 and 0.10 cm for cine-and sequential-modes, respectively, with a p-value of 0.02. The median D values were significantly different: 0.47 and 0.24 cm for cine-and sequential-modes, respectively, with a p-value < 0.001. Conclusions: Respiratory motion measurement may be more accurate and less susceptible to breathing irregularity in sequential-mode 4D-MRI than that in cine-mode 4D-MRI. C 2016 American Association of Physicists in Medicine. [http://dx

Investigation of the XCAT phantom as a validation tool in cardiac MRI tracking algorithms

“…In comparison to other studies which utilize the XCAT for simulation studies [26,34], we demonstrated how differing patient physiology could influence tracking accuracy. For the 20 virtual patients studied, the heart rate was the most influential anatomical parameter affecting the tracking accuracy.…”

“…to simulate realistic cardiac MRI on a virtual patient cohort of 40 digital phantoms [23], for the modeling of regional heart defects caused by ischemia with incorporation of a finite-element model [24] and in respirationfocused modeling applications. The respiration-focused modeling applications include the verification of reproducible patient-specific diaphragm and chest motion traces for lung cancer radiotherapy [25], the validation of novel 4D-MRI techniques which image respiratory motion [26] and an analysis of audiovisual biofeedback and gating on thoracic-abdominal 4D computed tomography [27].…”

A retrospective 4D‐MRI based on 2D diaphragm profiles for lung cancer patients

“…However, prospective methods usually require a long total scan time and produce a low contrast resolution. 27,30,[32][33][34] In contrast, conventional retrospective 4D-MRI methods 29,35,36 utilize a sorting method based on respiratory surrogate signals thus, requiring much shorter imaging time. But, breathing variation remains in the reconstruction process, often resulting in considerable image artefacts (i.e.…”

“…For instance, prospective imaging techniques 30,32,33 frequently require a long total scan time when breathing motion varies from breath to breath and the image quality can be highly subject to the size of the respiratory triggering window. 27,30,[32][33][34] On the other hand, retrospective image techniques 29,35,36 often suffer from considerable image artefacts (i.e. streak, duplicate, blurring and incompletion) due to breathing variation.…”

MRI-guidance for motion management in external beam radiotherapy: current status and future challenges

“…Different strategies were investigated to improve the performance of the external surrogate, either making use of audio-visual biofeedback (To et al 2016b) or advanced sorting (Liu et al 2015, Liang et al 2016, Tryggestad et al 2013d, Du et al 2015. As previously mentioned however, the use of internal breathing surrogates directly extracted from the acquired 2D images has been shown to increase robustness in organ motion description with respect to external surrogates (Stemkens et al 2015, Liu et al 2016a, Li et al 2017. Two main methods based on navigator sequences (Von Siebenthal et al 2007, Tokuda et al 2008, Wachinger et al 2012 or image-derived approaches (Cai et al 2011, Fontana et al 2016, Paganelli et al 2015c, Liu et al 2014a, Hui et al 2016, van de Lindt et al 2018b, van de Lindt et al 2018a, Uh, Khan and Hua 2016 are reported in the literature, relying on the acquisition of a navigator for sorting data, or on the derivation of the information directly from the data itself, respectively.…”